Acoustic Dimensions Research Articles

Segmental effects on the transmission of variability between articulation and acoustics

Previous research on articulatory-acoustic relations has generated conflicting results regarding the extent to which variability in articulation can be recovered from the acoustic signal (e.g., Guenther et al., 1999; Whalen etal., 2018). This study extends previous research probing the relationship between articulatory and acoustic variability by examining the extent to which individual differences in articulatory variability are recoverable from acoustics, and vice versa, for a set of American English consonants. A series of linear mixed effects regression models were fit to articulatory and acoustic data from tokens of /s/, /ʃ/, /l/, and /ɹ/ produced by 40 speakers in the Wisconsin X-Ray Microbeam Corpus (Westbury, 1994) to evaluate the extent to which the variability exhibited in one of these physical dimensions was recoverable from the signal in the other domain. The output of these statistical models was then compared to measurements of individual speakers’ variability along specific articulatory and acoustic dimensions to evaluate whether individual differences in variability were conveyed between articulation and acoustics. The results of the analyses suggest that the variability exhibited in one physical domain is to some extent recoverable from the other, although this capacity varies across segments and articulatory/acoustic dimensions. [Work supported by NIH.]

Auditory salience using natural scenes: An online study.

Salience is the quality of a sensory signal that attracts involuntary attention in humans. While it primarily reflects conspicuous physical attributes of a scene, our understanding of processes underlying what makes a certain object or event salient remains limited. In the vision literature, experimental results, theoretical accounts, and large amounts of eye-tracking data using rich stimuli have shed light on some of the underpinnings of visual salience in the brain. In contrast, studies of auditory salience have lagged behind due to limitations in both experimental designs and stimulus datasets used to probe the question of salience in complex everyday soundscapes. In this work, we deploy an online platform to study salience using a dichotic listening paradigm with natural auditory stimuli. The study validates crowd-sourcing as a reliable platform to collect behavioral responses to auditory salience by comparing experimental outcomes to findings acquired in a controlled laboratory setting. A model-based analysis demonstrates the benefits of extending behavioral measures of salience to broader selection of auditory scenes and larger pools of subjects. Overall, this effort extends our current knowledge of auditory salience in everyday soundscapes and highlights the limitations of low-level acoustic attributes in capturing the richness of natural soundscapes.

Preferences Offset Stressors in Determining Survivability

Pure stress-based models of health predict that accumulated stresses promote illnesses that result in lower life expectancies. However, in mixed subjective preference models, effects of stress, seen as negative preference, can potentially be offset by achievement of positive personal preferences. According to mixed preference models, preventive medicine strategies for promoting health can operate either by alleviating stress or by enhancing subjective preferences. Over many decades we developed a theory and practice of rational, psychoacoustically-driven architectural acoustic design of concert halls.1-3 The theory incorporates both negative acoustic annoyance attributes (stressors, negative preferences) and positive ones. Using self-assessment surveys of 30 dialysis patients in Kobe, Japan, we used the methodology to assess the effects of subjective preferences on delaying onset of dialysis treatment (dialysis onset age, DOA). Hayashi’s multivariate regression method (I) for nonparametric data 5,8 was used to estimate effects of reported factors. Of these, six factors proved predictive of DOA (p-values): better or worse interpersonal relations (0.003), decades of full-time work (0.050), alcohol consumption (0.031) according to individual preference, present noisy home environment (0.090), other pollution (0.060), smoking (0.115). Other factors were either weakly- or un- correlated: hospitalizations, house moves, past hypertension, proteinuria, sex, pet ownership, presence of bad odors, past noise pollution. Preventative measures that enhance subjective preferences may thus delay the need for dialysis.

Categorical Perception of Pitch Contours and Voice Onset Time in Mandarin-Speaking Adolescents With Autism Spectrum Disorders.

Purpose Previous studies have shown enhanced pitch and impaired time perception in individuals with autism spectrum disorders (ASD). However, it remains unclear whether such deviated patterns of auditory processing depending on acoustic dimensions would transfer to the higher level linguistic pitch and time processing. In this study, we compared the categorical perception (CP) of lexical tones and voice onset time (VOT) in Mandarin Chinese, which utilize pitch and time changes, respectively, to convey phonemic contrasts. Method The data were collected from 22 Mandarin-speaking adolescents with ASD and 20 age-matched neurotypical controls. In addition to the identification and discrimination tasks to test CP performance, all the participants were evaluated with their language ability and phonological working memory. Linear mixed-effects models were constructed to evaluate the identification and discrimination scores across different groups and conditions. Results The basic CP pattern of cross-boundary benefit when perceiving both native lexical tones and VOT was largely preserved in high-functioning adolescents with ASD. The degree of CP of lexical tones in ASD was similar to that in typical controls, whereas the degree of CP of VOT in ASD was greatly reduced. Furthermore, the degree of CP of lexical tones correlated with language ability and digit span in ASD participants. Conclusions These findings suggest that the unbalanced acoustic processing capacities for pitch and time can be generalized to the higher level linguistic processing in ASD. Furthermore, the higher degree of CP of lexical tones correlated with better language ability in Mandarin-speaking individuals with ASD.

Relationship between sound perception and acoustics of seat‐belt warning sound

AbstractUnderstanding the comprehensive sound perceptions is a major challenge in translating the affective needs and responses of drivers and passengers into the human‐centered design of seat‐belt warning sound (SBWS). Due to the various sound impressions of SBWS, sound quality has multiple impacts on driving safety, pleasure, stress, and so forth. This paper aims to derive a specified psychological factor structure for the sound perceptions of SBWS and to rebuild the connections between the psychological and acoustic attributes. Kansei (emotional or affective) evaluation is employed to collect the affective responses to 20 sound stimuli from 10 experts and 134 other participants. The perceived sound quality is expressed by 11 psychological attributes: “cheerful,” “interesting,” “lovely,” “comfortable,” “nervous,” “cordial,” “advanced,” “crisp,” “nostalgic,” “aroused,” and “weak.” Russell's emotional state model is also employed to map the sounds into a Pleasure–Arousal Kansei space for further analysis. For acoustic attributes, we measure amplitude, frequency, pause ratio, repetition speed, and element number, which are easy to be tuned according to the design guidelines listed as follows: First, a decrease in sound frequency results in sleepiness perception (less perceived urgency); second, fewer element (peak) number per cycle results in displeasure perception (less satisfaction); third, lower repetition speed results in pleasure and sleepiness perceptions simultaneously. The multiple linear regression model further indicates the quantitative psychoacoustic relationships, which helps sound designers to identify the key acoustic attributes and predict the affective responses for the human‐centered design of SBWS.

Enhancing robustness of zero resource children's speech recognition system through bispectrum based front-end acoustic features

Automatic recognition of children's speech for low resource languages is extremely challenging. This is due to the fact that speech data from child speakers for system training is unavailable in the case of such languages i.e., zero-resourced in terms of children's speech. Consequently, we are forced to decode children's speech on systems trained using a limited amount of adults' data. However, the acoustic mismatch between adults' and children's speech, such as pitch and speaking-rate differences, leads to highly degraded recognition rates. At the same time, since ASR systems embedded in smart devices are being used anywhere, effect of surrounding noise further degrades the recognition rates. Motivated by this fact, a noise robust front-end acoustic feature extraction approach exploiting bispectrum analysis is proposed in this paper. The proposed features are noise robust due to the inherent immunity of bispectrum towards additive noise. An added advantage of bispectrum analysis is reduced pitch sensitivity. This, in turn, helps reduce the aforementioned pitch-induced acoustic mismatch. Further to that, in order to deal with the unavailability of speech data from child speakers, we have explored the role of voice conversion through cycle-consistent generative adversarial network (CGAN) to modify the acoustic attributes of adults' data. Voice conversion via CGAN renders the adults' speech perceptually similar to children's speech as noted during the listening test. On augmenting the voice converted adults' speech into training, the ill-effects of the acoustic mismatch between adults' and children's speech is reduced to a large extent. Consequently, the recognition performance is significantly improved. The experimental evaluations presented in this paper demonstrate that the use of proposed features as well as CGAN-based voice conversion are highly suited for zero-resource children's speech recognition task under noisy conditions.

Dimension-selective attention and dimensional salience modulate cortical tracking of acoustic dimensions

Some theories of auditory categorization suggest that auditory dimensions that are strongly diagnostic for particular categories - for instance voice onset time or fundamental frequency in the case of some spoken consonants - attract attention. However, prior cognitive neuroscience research on auditory selective attention has largely focused on attention to simple auditory objects or streams, and so little is known about the neural mechanisms that underpin dimension-selective attention, or how the relative salience of variations along these dimensions might modulate neural signatures of attention. Here we investigate whether dimensional salience and dimension-selective attention modulate the cortical tracking of acoustic dimensions. In two experiments, participants listened to tone sequences varying in pitch and spectral peak frequency; these two dimensions changed at different rates. Inter-trial phase coherence (ITPC) and amplitude of the EEG signal at the frequencies tagged to pitch and spectral changes provided a measure of cortical tracking of these dimensions. In Experiment 1, tone sequences varied in the size of the pitch intervals, while the size of spectral peak intervals remained constant. Cortical tracking of pitch changes was greater for sequences with larger compared to smaller pitch intervals, with no difference in cortical tracking of spectral peak changes. In Experiment 2, participants selectively attended to either pitch or spectral peak. Cortical tracking was stronger in response to the attended compared to unattended dimension for both pitch and spectral peak. These findings suggest that attention can enhance the cortical tracking of specific acoustic dimensions rather than simply enhancing tracking of the auditory object as a whole.

Precolonial soundscapes of Swahili coastal towns in East Africa

ABSTRACT This paper aims to open the discussion on the characteristics of the acoustic landscapes in precolonial Swahili towns on the East African coast, where this theme to date remains unstudied. The paper focuses on assessing some aspects of the acoustic experience in the precolonial period of AD 1200–1600 respective to the towns and to coral-rag houses, which represent one type of building recorded on Swahili archaeological sites. Due to the limited preservation of buildings on the East African coast, and the fact that many of them have been deserted under the growing influence of Omani and European colonialism, both experimental and ethnoarchaeological studies could provide only limited information on any aspect of past sensory experience in these towns. Therefore, this paper defines some major characteristics of soundscapes in this region using analyses of the acoustic capacities and spatial dimensions of the Swahili built environment, while reflecting on selected themes that played a strong part in Swahili social environment, such as trade and Islam. The presented case study from sub-Saharan Africa aims to contribute to the global discussions on sensory experience in urban societies, where examples from coastal tropics are acutely needed.

All units are equal in humpback whale songs, but some are more equal than others.

Flexible production and perception of vocalizations is linked to an impressive array of cognitive capacities including language acquisition by humans, song learning by birds, biosonar in bats, and vocal imitation by cetaceans. Here, we characterize a portion of the repertoire of one of the most impressive vocalizers in nature: the humpback whale. Qualitative and quantitative analyses of sounds (units) produced by humpback whales revealed that singers gradually morphed streams of units along multiple acoustic dimensions within songs, maintaining the continuity of spectral content across subjectively dissimilar unit "types." Singers consistently produced some unit forms more frequently and intensely than others, suggesting that units are functionally heterogeneous. The precision with which singing humpback whales continuously adjusted the acoustic characteristics of units shows that they possess exquisite vocal control mechanisms and vocal flexibility beyond what is seen in most animals other than humans. The gradual morphing of units within songs that we observed is inconsistent with past claims that humpback whales construct songs from a fixed repertoire of discrete unit types. These findings challenge the results of past studies based on fixed-unit classification methods and argue for the development of new metrics for characterizing the graded structure of units. The specific vocal variations that singers produced suggest that humpback whale songs are unlikely to provide detailed information about a singer's reproductive fitness, but can reveal the precise locations and movements of singers from long distances and may enhance the effectiveness of units as sonar signals.

Phonetic convergence to non-native speech: Acoustic and perceptual evidence

While the tendency of speakers to align their speech to that of others acoustic-phonetically has been widely studied among native speakers, very few studies have examined whether natives phonetically converge to non-native speakers. Here we measured native Dutch speakers’ convergence to a non-native speaker with an unfamiliar accent in a novel non-interactive task. Furthermore, we assessed the role of participants’ perceptions of the non-native accent in their tendency to converge. In addition to a perceptual measure (AXB ratings), we examined convergence on different acoustic dimensions (e.g., vowel spectra, fricative CoG, speech rate, overall f0) to determine what dimensions, if any, speakers converge to. We further combined these two types of measures to discover what dimensions weighed in raters’ judgments of convergence. The results reveal overall convergence to our non-native speaker, as indexed by both perceptual and acoustic measures. However, the ratings suggest the stronger participants rated the non-native accent to be, the less likely they were to converge. Our findings add to the growing body of evidence that natives can phonetically converge to non-native speech, even without any apparent socio-communicative motivation to do so. We argue that our results are hard to integrate with a purely social view of convergence.

NHSS: A speech and singing parallel database

We present a database of parallel recordings of speech and singing, collected and released by the Human Language Technology (HLT) laboratory at the National University of Singapore (NUS), that is called NUS-HLT Speak–Sing (NHSS) database. We release this database11https://hltnus.github.io/NHSSDatabase/. to the public to support research activities, that include, but not limited to comparative studies of acoustic attributes of speech and singing signals, cooperative synthesis of speech and singing voices, and speech-to-singing conversion. This database consists of recordings of sung vocals of English pop songs, the spoken counterpart of lyrics of the songs read by the singers in their natural reading manner, and manually prepared utterance-level and word-level annotations. The audio recordings in the NHSS database correspond to 100 songs sung and spoken by 10 singers, resulting in a total of 7 h of audio data. There are 5 male and 5 female singers, singing and reading the lyrics of 10 songs each. In this paper, we discuss the design methodology of the database, analyze the similarities and dissimilarities in characteristics of speech and singing voices, and provide some strategies to address relationships between these characteristics for converting one to another. We develop benchmark systems, which can be used as reference for speech-to-singing alignment, spectral mapping, and conversion using the NHSS database.

Neural Encoding of Auditory Statistics.

The human brain extracts statistical regularities embedded in real-world scenes to sift through the complexity stemming from changing dynamics and entwined uncertainty along multiple perceptual dimensions (e.g., pitch, timbre, location). While there is evidence that sensory dynamics along different auditory dimensions are tracked independently by separate cortical networks, how these statistics are integrated to give rise to unified objects remains unknown, particularly in dynamic scenes that lack conspicuous coupling between features. Using tone sequences with stochastic regularities along spectral and spatial dimensions, this study examines behavioral and electrophysiological responses from human listeners (male and female) to changing statistics in auditory sequences and uses a computational model of predictive Bayesian inference to formulate multiple hypotheses for statistical integration across features. Neural responses reveal multiplexed brain responses reflecting both local statistics along individual features in frontocentral networks, together with global (object-level) processing in centroparietal networks. Independent tracking of local surprisal along each acoustic feature reveals linear modulation of neural responses, while global melody-level statistics follow a nonlinear integration of statistical beliefs across features to guide perception. Near identical results are obtained in separate experiments along spectral and spatial acoustic dimensions, suggesting a common mechanism for statistical inference in the brain. Potential variations in statistical integration strategies and memory deployment shed light on individual variability between listeners in terms of behavioral efficacy and fidelity of neural encoding of stochastic change in acoustic sequences.SIGNIFICANCE STATEMENT The world around us is complex and ever changing: in everyday listening, sound sources evolve along multiple dimensions, such as pitch, timbre, and spatial location, and they exhibit emergent statistical properties that change over time. In the face of this complexity, the brain builds an internal representation of the external world by collecting statistics from the sensory input along multiple dimensions. Using a Bayesian predictive inference model, this work considers alternative hypotheses for how statistics are combined across sensory dimensions. Behavioral and neural responses from human listeners show the brain multiplexes two representations, where local statistics along each feature linearly affect neural responses, and global statistics nonlinearly combine statistical beliefs across dimensions to shape perception of stochastic auditory sequences.

Revisiting the drivers of acoustic similarities in tropical anuran assemblages.

Acoustic signaling is key in mediating mate choice, which directly impacts individual fitness. Because background noise and habitat structure can impair signal transmission, the acoustic space of mixed-species assemblages has long been hypothesized to reflect selective pressures against signal interference and degradation. However, other potential drivers that received far less attention can drive similar outputs on the acoustic space. Phylogenetic niche conservatism and allometric constraints may also modulate species acoustic features, and the acoustic space of communities could be a side-effect of ecological assembly processes involving other traits (e.g., environmental filtering). Additionally, the acoustic space can also reflect the sorting of species relying on public information through extended communication networks. Using an integrative approach, we revisit the potential drivers of the acoustic space by addressing the distribution of acoustic traits, body size, and phylogenetic relatedness in tropical anuran assemblages across gradients of environmental heterogeneity in the Pantanal wetlands. We found the overall acoustic space to be aggregated compared with null expectations, even when accounting for confounding effects of body size. Across assemblages, acoustic and phylogenetic differences were positively related, while acoustic and body size similarities were negatively related, although to a minor extent. We suggest that acoustic partitioning, acoustic adaptation, and allometric constraints play a minor role in shaping the acoustic output of tropical anuran assemblages and that phylogenetic niche conservatism and public information use would influence between-assemblage variation. Our findings highlight an overlooked multivariate nature of the acoustic dimension and underscore the importance of including the ecological context of communities to understand drivers of the acoustic space.

Children's speaker verification in low and zero resource conditions

Our efforts towards developing an automatic speaker verification (ASV) system for child speakers are presented in this paper. For the majority of the languages, children's speech data for training the ASV system is either unavailable (zero-resource) or very limited (low-resource). Under low- and zero-resource conditions, developing an ASV system becomes a very challenging problem. To overcome this issue, we have studied the effectiveness of in-domain and out-of-domain data augmentation in this work. Speed and pitch modifications of children's speech are employed for synthetically creating data in the case of in-domain data augmentation. On the other hand, a limited amount of adults' speech is used when out-of-domain data augmentation is performed. Using adults' speech leads to severe acoustic mismatch due to dissimilarity in the attributes of speech data from adult and child speakers. To address this drawback, speech data from adult speakers are subjected to voice conversion (VC) to alter the acoustic attributes. A cycle-consistent generative adversarial network is used in this work for voice conversion. Voice conversion renders adults' speech perceptually similar to children's speech. The voice converted adults' data can then be used for augmentation, ensuring that the acoustic mismatch is minimal. To study the effectiveness of proposed data augmentation techniques experimentally, x-vector-based ASV system architecture is employed. At the same time, the role of i-vector is also studied in this paper. As a consequence of data augmentation, both equal error rate and minimum decision cost function are reduced significantly in low- and zero-resource conditions. At the same time, employing i-vectors for modeling speaker characteristics is noted to be superior. Finally, we have also presented a detailed study on the effect of data augmentation with child speakers' age variation.

The Interaction Between Timescale and Pitch Contour at Pre-attentive Processing of Frequency-Modulated Sweeps

Speech comprehension across languages depends on encoding the pitch variations in frequency-modulated (FM) sweeps at different timescales and frequency ranges. While timescale and spectral contour of FM sweeps play important roles in differentiating acoustic speech units, relatively little work has been done to understand the interaction between the two acoustic dimensions at early cortical processing. An auditory oddball paradigm was employed to examine the interaction of timescale and pitch contour at pre-attentive processing of FM sweeps. Event-related potentials to frequency sweeps that vary in linguistically relevant pitch contour (fundamental frequency F0 vs. first formant frequency F1) and timescale (local vs. global) in Mandarin Chinese were recorded. Mismatch negativities (MMNs) were elicited by all types of sweep deviants. For local timescale, FM sweeps with F0 contours yielded larger MMN amplitudes than F1 contours. A reversed MMN amplitude pattern was obtained with respect to F0/F1 contours for global timescale stimuli. An interhemispheric asymmetry of MMN topography was observed corresponding to local and global-timescale contours. Falling but not rising frequency difference waveforms sweep contours elicited right hemispheric dominance. Results showed that timescale and pitch contour interacts with each other in pre-attentive auditory processing of FM sweeps. Findings suggest that FM sweeps, a type of non-speech signal, is processed at an early stage with reference to its linguistic function. That the dynamic interaction between timescale and spectral pattern is processed during early cortical processing of non-speech frequency sweep signal may be critical to facilitate speech encoding at a later stage.

Developing children’s speech recognition system for low resource Punjabi language

Building an automatic speech recognition (ASR) system for children is a very challenging problem especially when the domain-specific data for training is absent or insufficient. In this paper, we present our efforts towards developing a children’s ASR system in Punjabi which a low-resourced language. To begin with, since speech data from children in the case of the Punjabi language is unavailable, we first created a small speech corpus consisting of data from both adult and child speakers. Next, an ASR system was developed on a mix of adults’ and children’s speech and tested on children’s speech. Due to the differences in acoustic attributes such as formant frequency, pitch, and speaking-rate differences between adults’ and children’s speech, the developed ASR system is observed to result in a highly degraded recognition rate. To reduce the acoustic mismatch, we have explored vocal-tract length normalization (VTLN), explicit pitch, and duration modification. All the three explored approaches are observed to be highly effective. To deal with training data scarcity, the role of prosody-modification-based out-of-domain data augmentation is studied. For that purpose, the pitch and speaking-rate of adults’ speech training set are explicitly changed to render it similar to children’s speech. The original and prosody modified data are then pooled together before learning the acoustic models. Significantly reduced error rates are observed by prosody-modification-based out-of-domain data augmentation. In addition to these, we have also studied the effect of varying the number of senones, the number of hidden nodes, and hidden layers as well as early stopping resulting in 32.1% of Relative Improvement (RI) in comparison to the baseline system with varied senones.

Distinct signatures of subjective confidence and objective accuracy in speech prosody

Whether speech prosody truly and naturally reflects a speaker's subjective confidence, rather than other dimensions such as objective accuracy, is unclear. Here, using a new approach combing psychophysics with acoustic analysis and automatic classification of verbal reports, we tease apart the contributions of sensory evidence, accuracy, and subjective confidence to speech prosody. We find that subjective confidence and objective accuracy are distinctly reflected in the loudness, duration and intonation of verbal reports. Strikingly, we show that a speaker's accuracy is encoded in speech prosody beyond their own metacognitive awareness, and that it can be automatically decoded from this information alone with performances up to 60%. These findings demonstrate that confidence and accuracy have separable prosodic signatures that are manifested with different timings, and on different acoustic dimensions. Thus, both subjective mental states of confidence, and objective states related to competence, can be directly inferred from this natural behavior.

The Learning Signal in Perceptual Tuning of Speech: Bottom Up Versus Top-Down Information.

Cognitive systems face a tension between stability and plasticity. The maintenance of long-term representations that reflect the global regularities of the environment is often at odds with pressure to flexibly adjust to short-term input regularities that may deviate from the norm. This tension is abundantly clear in speech communication when talkers with accents or dialects produce input that deviates from a listener's language community norms. Prior research demonstrates that when bottom-up acoustic information or top-down word knowledge is available to disambiguate speech input, there is short-term adaptive plasticity such that subsequent speech perception is shifted even in the absence of the disambiguating information. Although such effects are well-documented, it is not yet known whether bottom-up and top-down resolution of ambiguity may operate through common processes, or how these information sources may interact in guiding the adaptive plasticity of speech perception. The present study investigates the joint contributions of bottom-up information from the acoustic signal and top-down information from lexical knowledge in the adaptive plasticity of speech categorization according to short-term input regularities. The results implicate speech category activation, whether from top-down or bottom-up sources, in driving rapid adjustment of listeners' reliance on acoustic dimensions in speech categorization. Broadly, this pattern of perception is consistent with dynamic mapping of input to category representations that is flexibly tuned according to interactive processing accommodating both lexical knowledge and idiosyncrasies of the acoustic input.

Individual Differences in Categorization Gradience As Predicted by Online Processing of Phonetic Cues During Spoken Word Recognition: Evidence From Eye Movements.

Recent studies have documented substantial variability among typical listeners in how gradiently they categorize speech sounds, and this variability in categorization gradience may link to how listeners weight different cues in the incoming signal. The present study tested the relationship between categorization gradience and cue weighting across two sets of English contrasts, each varying orthogonally in two acoustic dimensions. Participants performed a four-alternative forced-choice identification task in a visual world paradigm while their eye movements were monitored. We found that (a) greater categorization gradience derived from behavioral identification responses corresponds to larger secondary cue weights derived from eye movements; (b) the relationship between categorization gradience and secondary cue weighting is observed across cues and contrasts, suggesting that categorization gradience may be a consistent within-individual property in speech perception; and (c) listeners who showed greater categorization gradience tend to adopt a buffered processing strategy, especially when cues arrive asynchronously in time.

Context-dependent phonetic enhancement of a phonation contrast in San Pablo Macuiltianguis Zapotec

This paper presents novel data from San Pablo Macuiltianguis Zapotec, a Sierra Juárez variety spoken in Oaxaca, Mexico. This language is ‘laryngeally complex’ (Silverman, 1997), exhibiting both contrastive tone and contrastive phonation. We examine the acoustic properties of the modal and checked vowels in this language, showing that this contrast is variably produced with several different acoustic cues. We analyze the distribution of these cues as an instance of phonetic enhancement and further show that the prosodic position of a given vowel determines which of several enhancement patterns is used. We argue that extant theories of phonetic enhancement, while able to explain the patterns described here, fall short of predicting the distribution of enhancing cues. We therefore propose that future models of phonetic enhancement could be expanded to predict patterns in which more than one acoustic dimension is available for phonetic enhancement.