1.1. Production and Perception: Is there a link?

Theories of sound change have long assumed that an individual’s perception and production systems must be connected in some way for an individual to perceive a change within their speech community and implement it in their own production repertoire. This is a necessary condition if we posit that changes propagate from individual to individual, though the extent to which this is true (or, under which circumstances) had not been directly explored until recently (see Beddor, 2015). In establishing groundwork for theories about phonetic and sound change, Beddor et al. (2018) examine the time course of speaker-listeners’ coarticulatory vowel nasalization in production (from aerodynamic measures) and perceptual patterns (with an eye-tracking paradigm) in American English. They demonstrate within-individual correlations across production and perception for this stable variation not only in the use of a cue but in the time-course of use: Those who produce early nasal flow in a vowel use temporally early nasalization to identify words.

Although there is a strong theoretical appetite for perceptual and productive repertoires to map neatly onto one another, only some investigations have found individual-level evidence for this connection (e.g., Zellou, 2017; Coetzee, Beddor, Shedden, Styler, & Wissing, 2018; Beddor et al., 2018; Fridland & Kendall, 2012; Kim & Clayards, 2019; Pinget et al., 2020; Voeten, 2020) while others have not (e.g., Kataoka, 2011; Grosvald & Corina, 2012; Schertz et al., 2015; Schultz et al., 2012; Kwon, 2015). Thus, the field has yet to come to a satisfying answer regarding the relevant conditions for matching or mismatching production-perception repertoires (see Yu & Zellou, 2019). Here, we briefly review some possible explanations for these cross-study discrepancies.

One common suggestion put forth to account for inconsistent findings is that the experimental tasks and measures used to assess a link between production and perception were not necessarily comparable, such that production and perception tasks may have in fact been measuring different constructs (see Zellou, 2017; Kim & Clayards, 2019; Grosvald & Corina, 2012). A related concern is that previous measures may not have been sensitive enough to capture similarities across domains (e.g., static versus dynamic measures, Beddor et al., 2018). These concerns point to a need for careful selection of tasks and variables for comparison. They also link to methodological concerns about validity and reliability in terms of how phonetic variables are assessed (e.g., acoustic measurements versus auditory coding; trained versus naive listeners; speakers versus non-speakers; Evans, Munson, & Edwards, 2018).

From a theoretical perspective, some posit that the context of variation, such as the stability of variation patterns in the community, has consequences for production-perception alignment. Beddor et al. (2018), for example, suggest that an individual’s link between perception and production is likely at its weakest during change when variants are in flux and socially-stratified, in comparison to stable, non-socially-indexed variation (see also Harrington, 2012). However, current empirical evidence does not obviously support this position. In terms of stable variation, while Beddor and colleagues do find a link between production and perception at the individual level for vowel nasalization (as does Zellou, 2017), a number of scholars investigating different types of coarticulatory variation failed to do so (e.g., Schultz et al., 2012 on VOT-f0 cue weighting in English; Schertz et al., 2015 on Korean L2 English VOT versus f0; Grosvald & Corina, 2012 on vowel-to-vowel coarticulation), though these direct comparisons may be inconclusive due to the aforementioned methodological differences.

Importantly, many recent studies of sound change do find evidence of individual-level links between domains, despite community-level mismatch (Coetzee et al., 2018; Kuang & Cui, 2018; Pinget et al., 2020; Voeten, 2020). On the surface, these findings run counter to the above prediction as individual-level production-perception relationships can indeed be found during changes-in-progress. Yet, it remains possible that the size of correlation is smaller or that a larger number of individuals demonstrate a lack of relationship, both compatible with an interpretation that the relationship is weaker during change than during stability. Overall, this highlights the need for more systematic, controlled comparison of individual production and perception patterns for variation in different contexts, crucially using comparable measures.

1.2. Production-perception alignment: What matters?

Beyond the simple existence of a production-perception connection, a co-occurring question pertains to the nature or direction of alignment. In studies of community change, alignment direction has been demonstrated to vary such that, at times, perception appears to lead in sound change while at other times, production appears more advanced. Some have called for attention to the trajectory and stage of change when examining production and perception, arguing that alignment patterns may depend on whether the change is in early or late stages. A slew of recent findings converge to support the notion that direction of misalignment may be yoked to the stage of the change.

Kuang and Cui (2018) documented two vowel changes in Southern Yi where phonation cues are shifting to formant cues. For the incipient /u/ change, all speaker groups were generally aligned: Phonation was the most important cue in both domains, but F1 was increasingly relied upon in perception. For the ongoing /e/ change, however, older speakers were misaligned, using phonation as the primary cue in production but F1 as the novel primary cue in perception. In contrast, younger speakers were categorized as ‘realigned,’ using the novel F1 cue in both domains. In sum, misalignment occurred during intermediate stages of change and perception led production for both early- and mid-stage change.

Pinget et al. (2020) show comparable results for regional bilabial stop and labiodental fricative devoicing mergers in Dutch, where perception tends to precede production for change in initial stages. Interestingly, their results indicate a reversal during later stages of change such that perception remained comparatively less merged for individuals whose change is near completion in production. In an investigation of a VOT-f0 cue weighting shift in Afrikaans, Coetzee et al. (2018) similarly found that younger speakers were generally ‘realigned’ at the individual level, but if they were misaligned, production was more advanced. This late-stage perception lag is consistent with research on vowel mergers showing that, based on expectations of the talker, listeners can utilize cues in perception that they do not distinguish in production (e.g., Hay, Warren, & Drager, 2006; Koops, Gentry, & Pantos, 2008).

Factors relating to the source of sound change may separately influence the manifestation of production-perception misalignment. Voeten (2020), for example, finds that sociolinguistic migrants from Belgium who moved to the Netherlands were variable in their approximation of Netherlandic vowels; in general, although production and perception were linked in this case, production seemed to lead perception. This suggests that differences may arise in production-perception mismatch between cases of internally-driven versus contact-driven changes. In other words, studies of second dialect acquisition (e.g., Voeten, 2020; Evans & Iverson, 2007) find that production appears to lead perception, at least in early stages. In other cases of presumably internal changes occurring across generations, perception leads at first (e.g., Kuang & Cui, 2018; Pinget et al., 2020) until the change reaches late stages.

Finally, the type of change may matter in the coordination of production and perception. Most prior studies investigated cue shifting (e.g., Coetzee et al., 2018; Kuang & Cui, 2018) or boundary shifting (e.g., Harrington et al., 2008; Kleber, Harrington, & Reubold, 2012) changes, with a focus on vowels. To quote Kuang and Cui (2018), does “production and perception have the same relationship across different languages, different types of sound change (e.g., merger, cue shifting, or boundary shifting), and different types of coarticulation?” (p. 196).

In the current study, we highlight mergers as an interesting case of change, unique because they represent a total loss of phonological contrast rather than simply a shifting of cues that maintain contrast. This comparatively drastic phonological change could lead to differences in behaviour surrounding production and perception. To the best of our knowledge, only one study of production and perception has been published on segmental mergers (Pinget et al., 2020), for which reported results agree with those of other studies. Prior studies on tone mergers in Hong Kong Cantonese also report a link between reduced distinction in production and slower responses in perception (Mok, Zuo, & Wong, 2013; Ou & Law, 2017). Here, we present an investigation of a set of consonant mergers in Hong Kong Cantonese, each with its own socio-historical profiles, to test the robustness of the perception-production link across different types of sound changes.

1.3. Consonant mergers in Hong Kong Cantonese

Hong Kong Cantonese (HKC) provides an interesting opportunity to study mergers, as a large set of consonantal (e.g., Wong, 1941; Zee, 1999a; To et al., 2015) and tonal mergers (e.g., Bauer, Cheung, & Cheung, 2003; Mok et al., 2013; Zhang, 2019) have emerged over the course of the last century. Moreover, the complex and ever-changing socio-political landscape surrounding Hong Kong has introduced a multitude of external influences on HKC, with consequences for the trajectory of these mergers. The last few decades, in particular, have seen rapid changes due to the transition of Hong Kong’s political status from a British colony to a Special Administrative Region under Chinese rule in 1997 (‘the handover’). While already a highly multilingual environment, one notable change is the increasing presence and influence of Mandarin in the city, alongside Cantonese and English, especially for younger generations (e.g., in the education system; Lee & Leung, 2012; Wang & Kirkpatrick, 2015; Wong, A., 2019). Whether contact with Mandarin has ultimately affected the HKC sound changes is unclear, though both convergence, such as reversing changes that are dissimilar to Mandarin (Bauer & Benedict, 1997), and divergence, for example maintaining HKC-specific changes that are linked to local identity (Whelpton, 1999), are conceivable. This latter possibility is particularly plausible given that many locals continue to identify as ‘Hong Kongers’ (as opposed to ‘Chinese’ or ‘Hong Kong-Chinese’) and specifically view Cantonese as central to this identity (Lai, 2001; Lai, 2011).

Another layer of complexity is that linguistic ideologies (e.g., the public media campaigns and school curriculum changes spearheaded by Professor Richard Ho Man-Wui, a prominent public scholar and professor of Chinese literature) have led to stigmatization of the innovative variants. The use of mergers is termed 懶音 laan5 jam1, which translates roughly to ‘lazy pronunciation’ (also variably denoted as ‘lazy accent,’ ‘lazy articulation,’ and ‘lazy sounds’). This notion is recognized by Hong Kongers in the present day (Chen, 2018), and is perhaps particularly salient to younger generations due to the introduction of Cantonese pronunciation in a standardized exam in 2007. This prompted official promotion of ‘proper Cantonese pronunciation’ on TV and radio, as well as in school activities (Lee & Leung, 2012). As a result of the prevailing prescriptivist approach linking conservative variants with standardness, clarity, and formality, a certain level of explicit awareness and attitudes about the various mergers is available to individuals; this may in turn legitimize hypercorrection to the ‘proper’ variant.

In Hong Kong, these external factors could have plausibly come together to stall or reverse the progression of the mergers, leading to stable variation or preservation of the conservative form in formal registers (e.g., Labov, 1994; Hickey, 2012). Though HKC consonant mergers have been the focus of a sizable number of sociolinguistic and phonetic production studies in the past (e.g., Bauer, 1982a, Zee, 1999a; To et al., 2015), little to no research appears to have revisited these consonant mergers in recent years. The most recent comprehensive study on the status of HKC consonant mergers is To et al. (2015), which reports on data collected in the early 2000s when the earliest post-handover generation were still children. While large in its sample of speakers, this study was limited in scope and too early to assess post-handover outcomes.

Against this background, the present investigation focuses on three consonant mergers in HKC: onset [n]→[l], syllabic [ŋ̩]→[m̩], and onset [ŋ]↔Ø. Table 1 provides examples. Despite surface similarities, they present a mix of phonological and socio-historical profiles, including differences in phonetic biases, functional load, cross-language correspondences, and metalinguistic awareness (for a detailed review of the historical trajectories, see To et al., 2015). This variation provides an opportunity to extend previous research on the production-perception link to a set of contrasting mergers in a single speech community, testing the extent to which predictions of production and perception hold across different types of sound change in the same individuals while using the same tasks and measures.

1.4. The present study

The present study investigates the production and perception of the [n]→[l], [ŋ̩]→[m̩], and [ŋ]↔Ø mergers across two generations in Hong Kong, examining both group-level and individual-level patterns. By studying phonetic variation and change in this context, we hope to contribute new insights to unresolved questions in the sound change literature, including those on the phonetic basis of sound change. Our research objectives are two-fold.

The first goal is to test how production-perception patterns generalize across sound changes with varying attributes. In doing so, we seek to clarify the factors that modulate the existence and nature of the production-perception link, for which evidence has been inconsistent. Characteristics that may be relevant include source of change (internal versus contact-induced), stage of change (e.g., early- versus late-stage), and type of change (shifting versus merging). The present study explores the comparison between three internally-driven consonant mergers within the same speaker-listeners using a consistent methodology. While [n]→[l] and [ŋ̩]→[m̩] appear to similarly be late-stage changes (compared to the mid-to-late stage [ŋ]→Ø) according to recent report, these mergers are further differentiated by a host of other factors. We interpret these case studies in the context of previous results that have focused on cue-shifting and boundary-shifting vowel changes, with particular attention to the results of Pinget et al. (2020) who studied a pair of consonant voicing mergers.

The second objective is to add to documentation on the progression of these mergers specifically in the post-handover era of Hong Kong, revisiting several open threads in the HKC literature. Hong Kongers who grew up in the years since 1997 have had vastly different formative experiences from preceding generations, including increased exposure to Mandarin and reinforcement of ‘proper pronunciation’ ideologies that brand the mergers as ‘lazy’ (Chen, 2018). What can we glean about the status of the mergers across generations, taking into account these shifts in the sociolinguistic landscape? Because this aspect of the study is descriptive in nature, we seek to generally explore the patterning of variant use across demographic groups. Nonetheless, because of the historical context of these mergers as sound change, we place special interest in the extent to which age co-varies with usage of each phonetic variant and/or degree of lexical contrast between each pair. Specifically, based on their documentation of children’s production patterns in the early-2000s, To et al. (2015) determined that the [n]→[l] and [ŋ̩]→[m̩] mergers were near completion while Ø-initial was gaining ground over [ŋ]. Do these patterns and their predicted trajectories hold out? Alongside providing a more recent picture of production norms, we contribute to this body of literature by adding a perceptual component through a word categorization task.

3.1. Production

3.1.1. [n]→[l] merger

Data for the [n]→[l] merger (n = 1158) were analyzed in a logistic mixed effects regression model with the probability of [l] productions ([l] = 1, [n] = 0) as the dependent measure. All categorical variables were sum coded (Historical Pattern: /l/ = 1, /n/ = –1; Talker Age: Older = 1, Younger = –1; Talker Gender: Male = 1, Female = –1) and entered as possible main effects and interactions. There were random intercepts for Subject and Item, with Historical Pattern as a by-subject random slope.⁴

The model output is summarized in Table 6. There was a significant intercept, and a significant effect of Historical Pattern. These results indicate that [l] productions are overall more likely, and that [l] productions are even more likely on words that are historically pronounced with /l/. These results are visualized in Figure 2, separated by the non-significant factors of Talker Age and Gender in order to transparently present the individual variation that is present. The figures present a barplot to indicate the group patterns, along with individual data points for each individual; these individual data points are somewhat transparent so that individual overlap is observable. Lines connect an individual’s data points for the two word classes. While the group averages indicate that both historically /l/ and /n/ words are usually pronounced with [l], Figure 2 illustrates how there is both group-level separation between historical categories (confirming the model result) and considerable variation on the individual level.

Table 6

Model output for [n] and [l] merger in production. Significant factors (α level = 0.05) are bolded.

	B	Standard Error	z-value	p-value
Intercept	2.4026	0.52	4.62	3.83E-06
Historical Pattern	1.1601	0.3818	3.038	0.00238
Age Group	0.2192	0.4088	0.536	0.59182
Gender	0.2537	0.4084	0.621	0.5344
Historical Pattern : Age Group	–0.297	0.2121	–1.4	0.16156
Historical Pattern : Gender	0.1822	0.2112	0.863	0.38839
Age Group : Gender	–0.0898	0.4077	–0.22	0.82567
Historical Pattern : Age Group : Gender	0.1713	0.2109	0.812	0.41668

Figure 2

Group means and individual data points for proportion [l] productions for historically /l/- and /n/-onset words, faceted by age and gender. The lines connecting data points connect values for an individual. The shading of the individual points is to allow the visualization of individual overlap.

To better visualize the individual-level data, we also present each individual’s mean proportion of the innovative variant for the two historical categories as a scatter plot in Figure 3. Here, the bottom right quadrant represents conservative contrastive productions ([n] for /n/ and [l] for /l/), the top right quadrant represents innovative merged productions ([l] for /n/, [l] for /l/), the bottom left represents hypercorrective merged productions ([n] for /n/, [n] for /l/), and the top left represents a fully flipped contrastive production ([l] for /n/, [n] for /l/). Most participants are clustered in the top right quadrant, realizing /n/ as [l] the majority (or all) of the time, though there is considerable variation ranging to fully historically contrastive for a small number of participants in the bottom right corner. Participants who lean conservative include a mix of older and younger individuals. Five participants who are mainly younger (two younger men, two younger women, and one older woman) appear relatively merged in the hypercorrective direction, realizing a majority of both /n/ and /l/ words as [n]. As expected, none are contrastive in the opposite-to-historical direction. This visual inspection of the individual variation further supports the non-significance of age and gender as a predictor of innovative variant productions.

Figure 3

Proportion [l] for historically /n/ items (y-axis) and historically /l/ items (x-axis) for each individual. Women are plotted with circles and men with triangles. Older speakers are in red and younger speakers in blue. The values have been jittered to minimize overlap.

3.1.2. [ŋ̩]→[m̩] merger

Data for the [ŋ̩]→[m̩] merger (n = 872) were analyzed with a logistic mixed effects regression model in an identical fashion to those for the [n]→[l] merger, with the variant-specific variables coded analogously (i.e., dependent variable as the probability of [m̩] productions: [m̩] = 1, [ŋ̩] = 0; Historical Pattern: /m̩/ = 1, /ŋ̩/ = –1).

The model output is summarized in Table 7. There was a significant intercept, along with significant effects of Historical Pattern, Age Group, and Gender. There were no significant interactions. The results are visualized in Figure 4 separated by Historical Pattern, Age Group, and Gender with the bars showing the group pattern, overlaid with individual results. These visualizations corroborate the statistical output. Overall, talkers are more likely to use [m̩] for both historical word classes, but the effect of Historical Pattern confirms that [m̩] is more likely for historically /m̩/ words. In addition, older speakers are more likely to show the innovative pattern, using higher rates of [m̩], while male participants are significantly more likely to use [m̩] than female participants.

Table 7

Model output for [ŋ̩] and [m̩] merger in production. Significant factors (α level = 0.05) are bolded.

	B	Standard Error	z-value	p-value
Intercept	3.21905	0.57616	5.587	2.31E-08
Historical Pattern	1.08923	0.49451	2.203	0.02762
Age Group	0.71872	0.36322	1.979	0.04784
Gender	1.14734	0.3618	3.171	0.00152
Historical Pattern : Age Group	–0.2848	0.21884	–1.301	0.19312
Historical Pattern : Gender	0.05902	0.21788	0.271	0.78649
Age Group : Gender	–0.03475	0.35812	–0.097	0.92271
Historical Pattern : Age Group : Gender	–0.04729	0.21276	–0.222	0.8241

Figure 4

Group means and individual data points for proportion [m̩] productions for historically syllabic /m̩/ and /ŋ̩/ words, faceted by age and gender. The lines connecting data points connect values for an individual. The shading of the individual points is to allow the visualization of individual overlap.

Figure 5 presents the individual proportion scatterplot for [ŋ̩]→[m̩], as described for [n]→[l]. The vast majority of participants are located in the top right quadrant, representing innovative productions where both /m̩/ and /ŋ̩/ are realized as [m̩] the majority of the time. Many individuals are fully merged, clustering in the top right corner. There is some variation in proportions of [m̩] productions, though no participants produce flipped categories, and two younger women produce a hypercorrective pattern (majority [ŋ̩] for both /ŋ̩/ and /m̩/). Overall, this visualization makes clear that the individuals who produce variable, conservative, or hypercorrective patterns are overwhelmingly younger women (along with some older women and younger men), confirming the model Age and Gender effects where women and younger participants skew towards producing [ŋ̩].

Figure 5

Proportion [m̩] for historically /ŋ̩/ items (y-axis) and historically /m̩/ items (x-axis) for each individual. Women are plotted with circles and men with triangles. Older speakers are in red and younger speakers in blue. The values have been jittered to minimize overlap.

3.1.3. [ŋ]↔Ø merger

Data for the [ŋ]↔Ø merger (n = 1023) were analyzed similarly to the two previous mergers with a logistic mixed effects regression model. The variant-specific variables were coded with null-initial assumed as the innovative variant (i.e., dependent variable as the probability of vowel-initial productions: Ø = 1, [ŋ] = 0; Historical Pattern: Ø = 1, [ŋ] = –1).

The model output is summarized in Table 8. There was a significant intercept, and a significant effect of Historical Pattern. The results are visualized in Figure 6 separated by Historical Pattern, along with the nonsignificant effects of Age Group and Gender. Again, the bars demonstrate the group pattern and individuals’ results are presented as a top layer. Participants are more likely to use [ŋ] for all of these lexical items, with the effect of Historical Pattern indicating that vowel initial productions are more likely on historically vowel initial words, but these are still, overall, unlikely. Some clearly prefer vowel-initial onsets, however; individuals from three of the four demographic groups use vowel-initial onsets 100% of the time for both historically vowel-initial and [ŋ]-initial word classes.

Table 8

Model output for vowel initial and initial [ŋ] merger in production. Significant factors (α level = 0.05) are bolded.

	B	Standard Error	z-value	p-value
Intercept	–2.83844	0.64677	–4.389	1.14E-05
Historical Pattern	0.58628	0.28279	2.073	0.0382
Age Group	0.43279	0.59628	0.726	0.468
Gender	0.60362	0.58385	1.034	0.3012
Historical Pattern : Age Group	0.10844	0.16359	0.663	0.5074
Historical Pattern : Gender	–0.09481	0.16497	–0.575	0.5655
Age Group : Gender	0.62266	0.58525	1.064	0.2874
Historical Pattern : Age Group : Gender	–0.22533	0.18756	–1.201	0.2296

Figure 6

Group means and individual data points for proportion vowel-initial productions for historically [ŋ]- and null-initial words, faceted by age and gender. The lines connecting data points connect values for an individual. The shading of the individual points is to allow the visualization of individual overlap.

These results can be seen more clearly in the individual scatterplot (Figure 7). Unlike the other two mergers, the vast majority of participants are located in the bottom left quadrant, representing merged productions where both historical null and [ŋ] are overwhelmingly realized as [ŋ]-initial, including many individuals who are fully merged (clustering in the bottom left corner). Although no age effect was detected in the model, visual inspection of the individual data provides some insight into trends of variation. Specifically, the few participants who show a comparatively conservative pattern (lower right quadrant) are all older while all but one of the participants who show merging towards null (top right quadrant) are younger.

Figure 7

Proportion vowel-initial productions for historically [ŋ]-initial items (y-axis) and historically null-initial items (x-axis) for each individual. Women are plotted with circles and men with triangles. Older speakers are in red and younger speakers in blue. The values have been jittered to minimize overlap.

3.2. Perception

3.2.1. [n]→[l] merger

Null responses were removed, accounting for just over 1.5% of the data. The remaining data (n = 3265) were fit to a logistic mixed effects regression model predicting the likelihood of a historical /l/ word response (/l/ = 1, /n/ = 0). Continuum step was centered and scaled, and Talker Age and Gender were sum coded (Age: Older = 1, Younger = –1; Talker Gender: Male = 1, Female = –1). Subject was a random effect with Step as a by-subject random slope.⁵

The model output is reported in Table 9, and the results are visualized in Figure 8. There was a significant intercept, indicating that /l/ word responses were more likely, and main effects of Step and Age. The interaction between Step and Age was also significant. While, overall, participant response functions varied predictably by continuum step with more [n]-like realizations receiving more /n/ word responses, younger listeners present comparatively more extreme responses at the continuum endpoints, resulting in a steeper response function.

Table 9

Model output for [n]→[l] merger in perception. Significant factors (α level = 0.05) are bolded.

	B	Standard Error	z-value	p-value
Intercept	–0.44226	0.11441	–3.866	0.000111
Step (centered)	–1.85118	0.23359	–7.925	2.28E-15
Age Group	0.28777	0.11327	2.54	0.01107
Gender	0.10879	0.11218	0.97	0.332137
Step : Age Group	0.69128	0.23094	2.993	0.002759
Step : Gender	0.1023	0.22859	0.448	0.654494
Age Group : Gender	0.05584	0.11223	0.498	0.618813
Step : Age Group : Gender	–0.1741	0.22868	–0.761	0.446471

Figure 8

Proportion /l/ word responses for the [n]→[l] merger by continuum step. Step 1 of the continuum is a canonical [l] pronunciation and Step 13 is a canonical [n] pronunciation. The dashed blue line and triangles represent the data of the younger listeners, while older listeners are shown in solid red lines and circles. The error bars show standard error.

To explore the individual differences in the discreteness of these lexical items, individual values were quantified using the by-subject contrast coefficient slope (CCS), following the methods provided by Casillas (2021). This value, which can be taken as a measure of category ‘crispness’ (Morrison, 2007; Casillas & Simonet, 2016), is an estimate of the slope of each individual’s sigmoid at its steepest point. More extreme values indicate more crisp or discrete perceptual categories, while values closer to zero are taken to indicate a less discrete contrast, which we interpret as evidence of a merger in this case. As a concept, this crispness value acknowledges that phonological categories can exist on a gradient in terms of their categorical contrasts (see, for example, Hall, 2013). These category crispness values were estimated by fitting new logistic regression models with continuum Step (centered and scaled) as the only fixed effect. The left panel in Figure 9 shows the individual values for the [n] and [l] contrast. There are two extreme outliers with crispness values below –5; both of these individuals had nearly discrete response functions such that the first six steps of the continuum were categorized 100% of the time as /l/ and the last six steps of the continuum was categorized 100% of the time as /n/. This contrasts with the majority of participants who had more gradient sigmoid functions. The central tendency of the value was negative (Mean = –0.35, Median = –0.10) and the range was substantial (–5.33, 0.09).⁶ These data, visualized in more fine-grained detail in Figure 10, suggest that at the individual level, the degree of category crispness varied considerably. Younger women represent the most variable demographic group, demonstrating a very flat distribution and including comparatively many individuals with crisper categorization; younger men show a similar pattern which is notably flatter than both older groups.

Figure 9

Histograms illustrating the distributions of category crispness values for the three continua.

Figure 10

Histograms illustrating the distribution of individual category crispness scores for the [n]→[l] merger continuum; only crispness scores between –0.6 to 0.3 are presented to show the variation amongst individuals excluding the two extreme outliers. Density plots are underlaid to represent the distribution per demographic group. Women (top) and men (bottom) are plotted separately while older speakers are colored red and younger speakers colored blue.

3.2.2. [ŋ̩]→[m̩] merger

To analyze the [ŋ̩]→[m̩] merger, null responses were removed, accounting for just over 2% of the data. The remaining data (n = 3248) were fit to a logistic mixed effects regression model predicting the likelihood of a historical /m/ word response (/m̩/ = 1, /ŋ̩/ =0). All other model specifications were the same as [n]→[l].

The model output is reported in Table 10, and results are visualized in Figure 11. There was a significant intercept, indicating that /m̩/ responses were more likely, and there were main effects of Step, a two-way interaction between Age and Gender, and a three-way interaction between Step, Age, and Gender. Older men (M = 0.64) and younger women (M = 0.62) were more likely than younger men (M = 0.54) and older women (M = 0.49) to categorize the continuum as /m̩/. These demographic variables interact with step, and Figure 11 makes clear that the perceptual changes by step are much smaller than those for the [n]→[l] merger. The word categorization functions suggest that all listener groups are quite advanced in the merger, with younger women presenting the biggest distinction between /m̩/ and /ŋ̩/.

Table 10

Model output for the [ŋ̩]→[m̩] merger in perception. Significant factors (α level = 0.05) are bolded.

	B	Standard Error	z-value	p-value
Intercept	0.41768	0.13979	2.988	0.002809
Step (centered)	–0.40383	0.10457	–3.862	0.000113
Age Group	–0.05142	0.13962	–0.368	0.712672
Gender	0.0954	0.13971	0.683	0.494698
Step : Age Group	0.15525	0.10419	1.49	0.136216
Step : Gender	0.13829	0.10425	1.327	0.184662
Age Group : Gender	0.36936	0.13979	2.642	0.008239
Step : Age Group : Gender	–0.2807	0.10455	–2.685	0.007257

Figure 11

Proportion /m̩/ word responses for the [ŋ̩]→[m̩] merger by continuum step with different panels for male and female listeners. Step 1 of the continuum is a canonical [m̩] pronunciation and Step 13 is a canonical [ŋ̩] pronunciation. The dashed blue line and triangles represent the data of the younger listeners, while older listeners are shown in solid red lines and circles. The error bars show standard error.

Individual differences in recognition performance for [ŋ̩]→[m̩] were also analyzed in terms of category crispness. The middle panel in Figure 9 presents the distribution of these values. The range of values is attenuated compared to [n]→[l] (–0.23, 0.08), and the measures of central tendency are lower (Mean = –0.03, Median = –0.014), indicating that the contrast is overall less crisp for /ŋ̩/ and /m̩/. Figure 12 additionally reveals that while most demographic groups accordingly present distributions sharply peaking near zero, younger women as a group present a flatter distribution with increased variability towards higher crispness values. The majority of values are negative, however, indicating consistency in the direction of the category distinction that does exist.

Figure 12

Histograms illustrating the distribution of individual category crispness scores for the [ŋ̩]→[m̩] merger continuum. Density plots are underlaid to represent the distribution per demographic group. Women (top) and men (bottom) are plotted separately while older listeners are colored red and younger listeners colored blue.

3.2.3. [ŋ-]↔Ø merger

Lastly, the responses to the [ŋ]↔Ø continua were analyzed in a similar manner. Null responses were removed, accounting for just over 1% of the data. The remaining data (n = 3277) were fit to a logistic mixed effects regression model predicting the likelihood of a historical vowel-initial word response (Ø = 1, /ŋ/ =0). All other model specifications were the same as above.

The model output is reported in Table 11, and the results are visualized in Figure 13. There was a significant intercept, indicating that [ŋ] responses were more likely, and there was a main effect of Step. As the two-way interaction between Step and Age (p = 0.05912) approached the threshold for statistical significance, we include it in Figure 13 for consideration. Younger listeners trended towards more categoricity in their response patterns.

Table 11

Model output for the [ŋ]↔Ø-initial model in perception. Significant factors (α level = 0.05) are bolded.

	B	Standard Error	z-value	p-value
Intercept	0.21985	0.09718	2.262	0.02368
Step (centered)	0.35784	0.13257	2.699	0.00695
Age Group	–0.06238	0.0971	–0.642	0.52062
Gender	–0.04629	0.09708	–0.477	0.63344
Step : Age Group	–0.25023	0.13259	–1.887	0.05912
Step : Gender	–0.16481	0.13245	–1.244	0.21341
Age Group : Gender	0.07286	0.09704	0.751	0.45271
Step : Age Group : Gender	0.12243	0.13234	0.925	0.3549

Figure 13

Proportion vowel-initial word responses for the [ŋ]↔Ø-initial merger by continuum step. Step 1 of the continuum is a canonical vowel-initial pronunciation and Step 13 is a canonical [ŋ] onset pronunciation. The dashed blue line and triangles represent the data of the younger listeners, while older listeners are shown in solid red lines and circles. The error bars show standard error.

Individual differences for [ŋ]↔Ø were also quantified in terms of category crispness. While the mean (Mean = 0.029) and median (Median = 0.009) both are positive, the range of values (–0.22, 0.31) spans 0 to a greater degree than those for the previous two continua. Individuals’ data for these continua are shown in the right panel of Figure 9. Not only do the values for [ŋ]↔Ø indicate that listeners are not at all crisp in their category boundary, the varying signs of the crispness value indicates that individuals differ in the direction of their categorization of these items. That is, individuals have different mappings of which lexical item is vowel-initial and which is [ŋ]-initial. Figure 14 indicates that younger women again stand out with more distributed scores, particularly including a slight skew towards crisper positive values. While younger men show a strongly peaked distribution centered on zero, there were also a few individuals who look rather different in showing relatively crisp categorization.

Figure 14

Histograms illustrating the distribution of individual category crispness scores for the [ŋ]↔Ø-initial merger continuum. Density plots are underlaid to represent the distribution per demographic group. Women (top) and men (bottom) are plotted separately while older listeners are colored red and younger listeners colored blue.

3.3. Production-Perception

To understand the relationship between perception and production at the individual level for the three mergers under investigation, we quantified the degree of mergedness for perception and production. Mergers in perception were quantified using the absolute value of the by-subject crispness values described above. Higher values indicate more discrete perceptual categories, while lower values are taken to indicate a merger of perceptual categories.

Mergers in production were quantified as the absolute value of the difference between proportions of the more novel pronunciation (i.e., [l], [m̩], null) for historical /l/, /m̩/, and null-onsets words and proportions of the more novel pronunciation for the historical /n/, /ŋ̩/, and [ŋ]-onset words. This quantification means that individuals who produce, for example, a full merger 100% of the time (e.g., 100% [l] for historical /l/ and /n/ words) will have an equivalent merger score as those who exclusively show hypercorrection (e.g., 0% [l] for historical /n/ and /l/ words; thus 100% [n] for both lexical classes) and those who exhibit a variable mix of pronunciations for both lexical sets (e.g., 50% [l] for historical /n/ and /l/ words). Crucially, however, participants of these types are demonstrating a lack of a reliable difference in pronunciation variants for the lexical sets, which we take as an indication of a merger of these categories at the lexical level.

Importantly, for the production-perception analysis, we removed the two perceptual crispness outliers (see Figure 9), leaving 47 individuals for consideration. We did so because, first, their values were so exceptionally different (values less than –5 compared to an overall CCS median of –0.021 and IQR of 0.081) that it was neither possible to conduct any reasonable comparison between them and the remaining data, nor within the remaining data due to the expanded range. Second, based on visual inspection of individual response curves, the extreme jump in numerical value appears not to be linearly reflective of actual change in categoricity given that the next highest values within a reasonable range (approximately 0.6) looked similar and highly categorical;⁷ as a result, although treating the next highest values as maximum crispness is a simplification, using them to represent strongly categorical perceptual responses is a fair representation of the data and exclusion of the outliers is not expected to alter conclusions.

Figure 15 visualizes the individual patterns for merger in perception and production for the three mergers. Merger in production is on the x-axis. For ease of interpretation, the x-axis is reversed in these visualizations to represent the time course of merger, which proceeds from 100% contrast (no merger) to 0% contrast (full merger). Merger in perception is on the y-axis, represented by absolute category crispness scaled to a range of zero to one.⁸ Low values along either dimension indicate a stronger merger, with values of zero indicating a complete merger of linguistic categories. A dashed line is included to represent the hypothetical fitted line if production and perception were perfectly correlated, assuming, as a simplification, the maximum value across all three mergers as maximum categoricity.

Figure 15

Degree of merger in perception (y-axis) versus production (x-axis) for the three mergers. Merger in perception is the absolute value of category crispness and the merger in production is quantified as the absolute value of the difference in the proportions of the novel pronunciation for the two lexical sets for each merger. The range of the x-axis is from 1 (fully contrastive) to 0 (fully merged) to reflect the time course of change. The solid lines represent fitted lines to the data while the dashed lines represent a hypothetical fitted line if production and perception were perfectly correlated.

These measures of merger in perception and production are moderately correlated for the [n]→[l] merger [t(47) = 4.10, r = 0.51, p = 0.0002]⁹ and [ŋ̩]→[m̩] merger [t(47) = 4.13, r = 0.52, p = 0.001]. These positive correlations are represented as negative in the plots due to x-axis reversal, but indicate the degree to which perception and production move in tandem. There was no relationship between merger in perception and production for the [ŋ]↔Ø merger [t(47) = –0.06, r = –0.009, p = 0.95]. The regression lines in the panels present these relationships. Note that the y-axes on these figures are uniform to illustrate the different distributions of crispness values, and this makes the strength of the correlation for [ŋ̩]→[m̩] look substantially less strong than for [n]→[l], which is not the case numerically.

To assess the direction of misalignment within an individual, we calculate the difference between scaled production and perception values per merger (DiffPP, following Pinget et al., 2020). Zero indicates completely aligned production and perception, regardless of whether individuals are fully merged, fully contrastive, or at an intermediate value. Scores above zero represent individuals whose production is more contrastive (less merged) than perception while scores below zero represent individuals whose perception is more contrastive (less merged) than production. Visualized in Figure 16, this provides another way to look at the data, in essence representing the direction and distance of each individual from the hypothetical perfect correlation line in Figure 15.

Figure 16

DiffPP scores, calculated as the difference of production and perception measures (y-axis) versus production (x-axis, reversed) for the three mergers. DiffPP scores above zero represent individuals whose production is more contrastive (less merged) than perception while scores below zero represent individuals whose perception is more contrastive (less merged) than production.

The left panel in Figure 15 illustrates the reliable correlation between merger in /n/ and /l/ production and perceptual category crispness in a forced choice task of word selection. Individuals who make smaller differences in their rates of [l] production for historical /l/ and /n/ categories are more likely to be merged in perception; this is seen as the clustering in the bottom right corner. At the same time, the subset of participants who show a difference in [l] pronunciation rates for historical /n/ and /l/ words are more likely to exhibit a crisper perceptual contrast. Nevertheless, the relationship between production and perception is far from perfect. As seen in the left panel of Figure 16, many individuals show production-perception misalignment by falling above or below the zero line. A number of observations are notable. First, multiple individuals who produce little to no contrast (on the right side of the plot) fall below zero, demonstrating contrast in perception despite none in production. Conversely, misaligned individuals who produce some contrast (roughly greater than 0.2) tend to fall above zero, demonstrating more contrast in production than perception. In other words, perception appears to lead production in merger, but when merger is (nearly) complete in production, perception appears to lag (i.e., retain contrast). Finally, age appears to play a role such that younger individuals appear more likely to show lower DiffPP scores relative to older individuals with similar production patterns. In particular, three younger women defy the general trend, showing intermediate production contrast but with comparatively greater perceptual categoricity than production.

The middle panel in Figure 15 illustrates the reliable correlation between merger in /m̩/ and /ŋ̩/ production and perceptual category crispness in a forced choice task of word selection. Specifically, individuals who exhibit a smaller difference in their rates of production of the more innovative [m̩] for historically /m̩/ and /ŋ̩/ words are more likely to be merged in perception, while those producing larger contrasts were more likely to show crisper perceptual distinction. The distribution of perceptual crispness values is contracted compared to those values for the [n]→[l] merger, indicating that, overall, this contrast is less perceptually robust.¹⁰ Again, while there is a significant correlation, the relationship is not isomorphic: There is substantial variability in the alignment of production of these variants and listeners’ ability to systematically distinguish the lexical items by historical category in perception. Taking the maximum perceptual crispness value for [n]→[l] as the upper limit,¹¹ the overall pattern in the middle panel of Figure 16 is that individuals who are not fully merged show more contrastiveness in production than perception. Nearly all participants fall roughly at or above zero; a few individuals do show a small degree of misalignment towards perception, but otherwise, if not aligned, perception leads production. In addition, younger participants tend to show lower DiffPP scores, indicating less alignment skew towards production contrast.

Lastly, the third panel of Figure 15 illustrates the lack of correlation between the merger of historically [ŋ] and vowel-initial items in production and perceptual category crispness in a forced choice task of word selection (of aak1 ‘shake’ and ngaak1 ‘deceive,’ specifically). The range of perceptual crispness values are similar to those for [ŋ̩]→[m̩], but the production range is more limited. This reaffirms the production results where individuals either mainly produce [ŋ] or null-initial. In Figure 16, the vast majority of participants merge [ŋ] and null-initial in both production and perception but those who do not follow a similar pattern to [n]→[l]: Those who produce little to no contrast fall below zero (perception lags behind production) while misaligned individuals who produce some contrast (roughly greater than 0.2) fall above zero (perception leads production). Further, there appears to be an age-based pattern whereby younger individuals make up the majority of production-merged individuals who fall below zero, showing a contrast in perception despite none in production.

4.1. Past versus present in production

In To et al. (2015), the [n]→[l] merger appeared near-complete in both adults and children (mean rates of [l] for /n/ around 94%), but in the current data, /n/ is realized as [l] between 54% (younger women) to 71% (older women) of the time. Within each group, speakers also varied considerably as to whether they realized /n/ as [l], ranging from 0% to 100%—in fact, 13 of the 49 speakers were fully merged. Further, no age or gender pattern was evident for speakers who were mainly contrastive. This suggests that the linguistic situation is more complicated than a simple story of change-in-progress where the contrast is maintained by the older generation. In addition to variation in /n/, there was variation in the amount of [l] produced for /l/, which has been generally ignored in previous literature due to the assumption that /l/ was not changing. That some speakers produce a significant amount of [n] for /l/ (up to 100% in one speaker’s case) confirms that [l]→[n] ‘hypercorrection’ does exist, contrary to Bourgerie’s (1990) assertion. For at least these individuals, it seems that the social meaning of ‘properness’ indexed to [n] (Pan, 1981) can be applied to both historical /n/ and /l/. Altogether, this suggests that the two variants [l] and [n] are dually-mapped to the same lexical items regardless of historical lexical class (Samuel & Larraza, 2015); this is indicative of a merger at the lexical level (Soo & Babel, 2020). Listeners have implicit knowledge—and possibly explicit awareness, given the pronunciation campaigns and social meaning attributed to the variants—that /n/ and /l/ are merged, but they lack the knowledge of which items were historically /l/, allowing for both [n] and [l] pronunciation variants for both lexical classes.

The [ŋ̩]→[m̩] merger was likewise reported by To et al. (2015) to be near-complete. While older adults (particularly men) show comparable or slightly decreased production of [m̩] for /ŋ̩/ in the current data (70–100% now versus 91–100% before), the younger cohort shows clearly decreased [m̩] usage roughly 15 years later (50–75% now versus 97–100% before). While interactions with age were not statistically significant, this result seems linked to trending differences in historical category merger across demographic groups: Nearly all older men are fully merged (92.6% [m̩] for /ŋ̩/, 98.8% [m̩] for /m̩/), many older women (71.6% [m̩] for /ŋ̩/, 90.5% [m̩] for /m̩/) and younger men (77.6% [m̩] for /ŋ̩/, 97.8% [m̩] for /m̩/) are relatively merged, but a sizable number of younger women make moderate-to-large contrasts (50.4% [m̩] for /ŋ̩/, 82.9% [m̩] for /m̩/). We additionally see gender differences in the preferred variant influenced by some women using high rates of both hypercorrective and conservative [ŋ̩]. Again, this behaviour indicates dual-mapping of [ŋ̩] to both historical /ŋ̩/ and /m̩/ lexical items, implying a certain degree of lexical merger.

For the [ŋ]↔Ø merger, children in To et al. (2015) produced more null onsets for both historical [ŋ] and null-initial (65.0% and 94.2%) while adults used the historical variants more often (37.5% and 68.7%). Yet, rather than a continuing trend of increased null, the current findings indicate that all groups produce less null-initial for both historical categories, at mean rates below 33.6% null (i.e., above 66.4% [ŋ]). Individual patterns show that there is large variation in behaviour of merging and choice of variant that, to a certain degree, pattern relative to age. Descriptively, those who show a higher degree of merger or are merged to null-initial are more likely younger, while those who maintain distinction between lexical classes are more likely older. Thus, while merger of the [ŋ]- and Ø-initial lexical classes may indeed have progressed, variant preference seems to have reversed dramatically.

4.2. Perception versus production in the community

Unlike production, a general theme in perception is that younger participants, particularly women, responded to historical lexical classes more categorically than older participants, though the degree of categoricity was objectively low for mergers involving [ŋ].¹⁵ Considering that age effects are not robustly supported by evidence in production, how can the perceptual age effects be interpreted? Younger listeners have had more exposure to the historical contrasts due to growing up with ‘proper pronunciation’ prescriptivism and language contact with Mandarin. One possibility is that, due to these experiences, they may have adapted to flexibly recognize the contrast in perception, regardless of whether they make a contrast between the two in their own productions (see Samuel & Larraza, 2015 on adaptation to variable pronunciations or ‘errors’; Sumner & Samuel, 2009 on covert experience with pronunciation variants on word recognition timing). Cognitively, this would be a dual-mapping of two pronunciation variants to a single phonological or lexical category for a style or register difference. This accommodation to phonetic variation is akin to interpretations of late-stage sound changes where perception ‘lags’ behind production due to the more advanced (e.g., younger) listeners’ need to maintain these representations to cope with speech produced by less advanced (e.g., older) speakers (see Pinget et al., 2020; Coetzee et al., 2018). In other words, they are flexible in perception while showing stability in production.

Another possibility is that, rather than simply demonstrating perceptual flexibility, younger speaker-listeners are in fact beginning to reverse the mergers in their recognition of lexical items, prior to showing clear signs of reversal in production. That is, a phonological change across generations may truly be occurring, where perception leads production in the opposition direction to the historical change. As suggested earlier, this explanation could align with qualitative age-based trends found in [ŋ̩]→[m̩] production. Only future investigations on the continuing trajectory of these variants can shed light on these open questions.

An alternative explanation does not rely on listeners’ decontextualized phonological representations but involves social representations construed from the model speaker’s voice. That is, differences may have arisen due to younger listeners perceiving the model speaker as a peer while older listeners perceived the same speaker as younger (Hay et al., 2006; Koops et al., 2008). Specifically, if there is an association between the younger generation and increased ‘lazy pronunciation’ held by older speakers (see discussion in Lin et al., 2021), we might expect that younger listeners (without such an association) perceive the stimuli more veridically while older listeners perceive the stimuli with less distinction. This possibility cannot be teased apart from other possible interpretations and must be left to future research.

4.3. Individual evidence for the production-perception link

Moving on to the production-perception link, our individual-level production-perception results reveal a link between production and perception for two consonantal mergers, corroborating recent positive findings from the sound change literature. In particular, it allows us to more confidently generalize the findings from Pinget et al. (2020) that a production-perception link can be found for consonantal mergers, just like more frequently-studied types of vowel-related sound change. Given the rather different properties of mergers to shifting-type changes (e.g., loss of contrast), the consistency of detecting an individual-level production-perception relationship is interesting and strengthens the claim of an underlying mechanistic link between systems that drives sound change.

On the contrary, no production-perception correlation was found for the [ŋ]↔Ø merger. Since the other two merger pairs demonstrated a correlation, the type of change (i.e., merger rather than cue shifting, for example) cannot be the constraining factor, contributing evidence against the hypothesis that production-perception relationships vary by type of change. Still, it is possible that the specific nature of this change is relevant. That is, the other two mergers are ‘standard’ contrast-loss mergers, unlike [ŋ]↔Ø which was originally allophonic and exhibited bidirectional merging. The nature of this change (including the changes in direction) may have contributed to the apparently unlinked representations. Given this, it may be beneficial for future research to consider more fine-grained variability among types of change and how it may influence the existence of a production-perception link. We additionally note that these findings could have resulted from the choice of perceptual stimuli and task, which involved lexical identification between items in a purported minimal pair that did not follow historical tone allophony patterns (i.e., involved an exception). With the current data, it is not possible to tease apart whether this null effect is due to the nature of this particular merger or aspects of the experiment. Future work would benefit from examining the [ŋ]↔Ø merger further in perception.

4.4. Direction of production-perception misalignment

Despite correlation differences, similar patterns of misalignment were uncovered across all three merger pairs. In general, individuals making a contrast in production showed comparatively less perceptual contrast, indicating that perceptual merger is more advanced than production merger. On the other hand, many individuals with nearly or fully merged production for [n]→[l] and [ŋ]↔Ø—if not ‘realigned’ through full merger in production and perception—in fact show evidence of categoricity in perception; this suggests that at these late stages of production merger, perception is less advanced, or lagging. Given the data at hand, these results fall in line with previous reports of production-perception misalignment with regards to stage of change (Pinget et al., 2020; Coetzee et al., 2018). However, the switch from perception-led to production-led change was reported in Pinget et al. (2020) to be roughly at the halfway point of merger while here, only those who were nearly or fully merged exhibited production leading perception. Whether this difference relates to the fact that the present mergers appear to have reached a state of socially conditioned variation rather than continued merger or whether such a pattern is dependent on the particular situation requires further investigation.

In addition, younger participants on the whole tend towards less misalignment in the direction of production contrast and/or more in the direction of perceptual contrast. This confirms that community-level perceptual and production results, where younger individuals showed more contrast in perception, can be sourced to the individual level. A final observation is noteworthy. Unlike the other two mergers, few individuals showed misalignment in the direction of perceptual contrast for the [ŋ̩]→[m̩] merger, even for those merged in production. Why does this difference arise? While speculative, it seems conceivable that [ŋ̩]→[m̩] operates on a reduced perceptual scale due to the lack of acoustic-perceptual salience for nasals (Harnsberger, 2000; Narayan, 2008); if so, a different approach to assessing misalignment may be needed in future in work that attempts to compare across multiple cases of variation and change.