Perception of nonnative tonal contrasts by Mandarin-English and English-Mandarin sequential bilinguals

This study examined the role of acquisition order and crosslinguistic similarity in influencing transfer at the initial stage of perceptually acquiring a tonal third language (L3). Perception of tones in Yoruba and Thai was tested in adult sequential bilinguals representing three different first (L1) and second language (L2) backgrounds: L1 Mandarin-L2 English (MEBs), L1 English-L2 Mandarin (EMBs), and L1 English-L2 intonational/non-tonal (EIBs). MEBs outperformed EMBs and EIBs in discriminating L3 tonal contrasts in both languages, while EMBs showed a small advantage over EIBs on Yoruba. All groups showed better overall discrimination in Thai than Yoruba, but group differences were more robust in Yoruba. MEBs’ and EMBs’ poor discrimination of certain L3 contrasts was further reflected in the L3 tones being perceived as similar to the same Mandarin tone; however, EIBs, with no knowledge of Mandarin, showed many of the same similarity judgments. These findings thus suggest that L1 tonal experience has a particularly facilitative effect in L3 tone perception, but there is also a facilitative effect of L2 tonal experience. Further, crosslinguistic perceptual similarity between L1/L2 and L3 tones, as well as acoustic similarity between different L3 tones, play a significant role at this early stage of L3 tone acquisition.Published versio

The phonetics of second language learning and bilingualism

This chapter provides an overview of major theories and findings in the field of second language (L2) phonetics and phonology. Four main conceptual frameworks are discussed and compared: the Perceptual Assimilation Model-L2, the Native Language Magnet Theory, the Automatic Selection Perception Model, and the Speech Learning Model. These frameworks differ in terms of their empirical focus, including the type of learner (e.g., beginner vs. advanced) and target modality (e.g., perception vs. production), and in terms of their theoretical assumptions, such as the basic unit or window of analysis that is relevant (e.g., articulatory gestures, position-specific allophones). Despite the divergences among these theories, three recurring themes emerge from the literature reviewed. First, the learning of a target L2 structure (segment, prosodic pattern, etc.) is influenced by phonetic and/or phonological similarity to structures in the native language (L1). In particular, L1-L2 similarity exists at multiple levels and does not necessarily benefit L2 outcomes. Second, the role played by certain factors, such as acoustic phonetic similarity between close L1 and L2 sounds, changes over the course of learning, such that advanced learners may differ from novice learners with respect to the effect of a specific variable on observed L2 behavior. Third, the connection between L2 perception and production (insofar as the two are hypothesized to be linked) differs significantly from the perception-production links observed in L1 acquisition. In service of elucidating the predictive differences among these theories, this contribution discusses studies that have investigated L2 perception and/or production primarily at a segmental level. In addition to summarizing the areas in which there is broad consensus, the chapter points out a number of questions which remain a source of debate in the field today.https://drive.google.com/open?id=1uHX9K99Bl31vMZNRWL-YmU7O2p1tG2wHhttps://drive.google.com/open?id=1uHX9K99Bl31vMZNRWL-YmU7O2p1tG2wHhttps://drive.google.com/open?id=1uHX9K99Bl31vMZNRWL-YmU7O2p1tG2wHAccepted manuscriptAccepted manuscrip

Tone classification of syllable -segmented Thai speech based on multilayer perceptron

Thai is a monosyllabic and tonal language. Thai makes use of tone to convey lexical information about the meaning of a syllable. Thai has five distinctive tones and each tone is well represented by a single F0 contour pattern. In general, a Thai syllable with a different tone has a different lexical meaning. Thus, to completely recognize a spoken Thai syllable, a speech recognition system has not only to recognize a base syllable but also to correctly identify a tone. Hence, tone classification of Thai speech is an essential part of a Thai speech recognition system.;In this study, a tone classification of syllable-segmented Thai speech which incorporates the effects of tonal coarticulation, stress and intonation was developed. Automatic syllable segmentation, which performs the segmentation on the training and test utterances into syllable units, was also developed. The acoustical features including fundamental frequency (F0), duration, and energy extracted from the processing syllable and neighboring syllables were used as the main discriminating features. A multilayer perceptron (MLP) trained by backpropagation method was employed to classify these features. The proposed system was evaluated on 920 test utterances spoken by five male and three female Thai speakers who also uttered the training speech. The proposed system achieved an average accuracy rate of 91.36%

Chinese Tones: Can You Listen With Your Eyes?:The Influence of Visual Information on Auditory Perception of Chinese Tones

CHINESE TONES: CAN YOU LISTEN WITH YOUR EYES? The Influence of Visual Information on Auditory Perception of Chinese Tones YUEQIAO HAN Summary Considering the fact that more than half of the languages spoken in the world (60%-70%) are so-called tone languages (Yip, 2002), and tone is notoriously difficult to learn for westerners, this dissertation focused on tone perception in Mandarin Chinese by tone-naïve speakers. Moreover, it has been shown that speech perception is more than just an auditory phenomenon, especially in situations when the speaker’s face is visible. Therefore, the aim of this dissertation is to also study the value of visual information (over and above that of acoustic information) in Mandarin tone perception for tone-naïve perceivers, in combination with other contextual (such as speaking style) and individual factors (such as musical background). Consequently, this dissertation assesses the relative strength of acoustic and visual information in tone perception and tone classification. In the first two empirical and exploratory studies in Chapter 2 and 3 , we set out to investigate to what extent tone-naïve perceivers are able to identify Mandarin Chinese tones in isolated words, and whether or not they can benefit from (seeing) the speakers’ face, and what the contribution is of a hyperarticulated speaking style, and/or their own musical experience. Respectively, in Chapter 2 we investigated the effect of visual cues (comparing audio-only with audio-visual presentations) and speaking style (comparing a natural speaking style with a teaching speaking style) on the perception of Mandarin tones by tone-naïve listeners, looking both at the relative strength of these two factors and their possible interactions; Chapter 3 was concerned with the effects of musicality of the participants (combined with modality) on Mandarin tone perception. In both of these studies, a Mandarin Chinese tone identification experiment was conducted: native speakers of a non-tonal language were asked to distinguish Mandarin Chinese tones based on audio (-only) or video (audio-visual) materials. In order to include variations, the experimental stimuli were recorded using four different speakers in imagined natural and teaching speaking scenarios. The proportion of correct responses (and average reaction times) of the participants were reported. The tone identification experiment presented in Chapter 2 showed that the video conditions (audio-visual natural and audio-visual teaching) resulted in an overall higher accuracy in tone perception than the auditory-only conditions (audio-only natural and audio-only teaching), but no better performance was observed in the audio-visual conditions in terms of reaction time, compared to the auditory-only conditions. Teaching style turned out to make no difference on the speed or accuracy of Mandarin tone perception (as compared to a natural speaking style). Further on, we presented the same experimental materials and procedure in Chapter 3 , but now with musicians and non-musicians as participants. The Goldsmith Musical Sophistication Index (Gold-MSI) was used to assess the musical aptitude of the participants. The data showed that overall, musicians outperformed non-musicians in the tone identification task in both auditory-visual and auditory-only conditions. Both groups identified tones more accurately in the auditory-visual conditions than in the auditory-only conditions. These results provided further evidence for the view that the availability of visual cues along with auditory information is useful for people who have no knowledge of Mandarin Chinese tones when they need to learn to identify these tones. Out of all the musical skills measured by Gold-MSI, the amount of musical training was the only predictor that had an impact on the accuracy of Mandarin tone perception. These findings suggest that learning to perceive Mandarin tones benefits from musical expertise, and visual information can facilitate Mandarin tone identification, but mainly for tone-naïve non-musicians. In addition, performance differed by tone: musicality improves accuracy for every tone; some tones are easier to identify than others: in particular, the identification of tone 3 (a low-falling-rising) proved to be the easiest, while tone 4 (a high-falling tone) was the most difficult to identify for all participants. The results of the first two experiments presented in chapters 2 and 3 showed that adding visual cues to clear auditory information facilitated the tone identification for tone-naïve perceivers (there is a significantly higher accuracy in audio-visual condition(s) than in auditory-only condition(s)). This visual facilitation was unaffected by the presence of (hyperarticulated) speaking style or the musical skill of the participants. Moreover, variations in speakers and tones had effects on the accurate identification of Mandarin tones by tone-naïve perceivers. In Chapter 4 , we compared the relative contribution of auditory and visual information during Mandarin Chinese tone perception. More specifically, we aimed to answer two questions: firstly, whether or not there is audio-visual integration at the tone level (i.e., we explored perceptual fusion between auditory and visual information). Secondly, we studied how visual information affects tone perception for native speakers and non-native (tone-naïve) speakers. To do this, we constructed various tone combinations of congruent (e.g., an auditory tone 1 paired with a visual tone 1, written as AxVx) and incongruent (e.g., an auditory tone 1 paired with a visual tone 2, written as AxVy) auditory-visual materials and presented them to native speakers of Mandarin Chinese and speakers of tone-naïve languages. Accuracy, defined as the percentage correct identification of a tone based on its auditory realization, was reported. When comparing the relative contribution of auditory and visual information during Mandarin Chinese tone perception with congruent and incongruent auditory and visual Chinese material for native speakers of Chinese and non-tonal languages, we found that visual information did not significantly contribute to the tone identification for native speakers of Mandarin Chinese. When there is a discrepancy between visual cues and acoustic information, (native and tone-naïve) participants tend to rely more on the auditory input than on the visual cues. Unlike the native speakers of Mandarin Chinese, tone-naïve participants were significantly influenced by the visual information during their auditory-visual integration, and they identified tones more accurately in congruent stimuli than in incongruent stimuli. In line with our previous work, the tone confusion matrix showed that tone identification varies with individual tones, with tone 3 (the low-dipping tone) being the easiest one to identify, whereas tone 4 (the high-falling tone) was the most difficult one. The results did not show evidence for auditory-visual integration among native participants, while visual information was helpful for tone-naïve participants. However, even for this group, visual information only marginally increased the accuracy in the tone identification task, and this increase depended on the tone in question. Chapter 5 is another chapter that zooms in on the relative strength of auditory and visual information for tone-naïve perceivers, but from the aspect of tone classification. In this chapter, we studied the acoustic and visual features of the tones produced by native speakers of Mandarin Chinese. Computational models based on acoustic features, visual features and acoustic-visual features were constructed to automatically classify Mandarin tones. Moreover, this study examined what perceivers pick up (perception) from what a speaker does (production, facial expression) by studying both production and perception. To be more specific, this chapter set out to answer: (1) which acoustic and visual features of tones produced by native speakers could be used to automatically classify Mandarin tones. Furthermore, (2) whether or not the features used in tone production are similar to or different from the ones that have cue value for tone-naïve perceivers when they categorize tones; and (3) whether and how visual information (i.e., facial expression and facial pose) contributes to the classification of Mandarin tones over and above the information provided by the acoustic signal. To address these questions, the stimuli that had been recorded (and described in chapter 2) and the response data that had been collected (and reported on in chapter 3) were used. Basic acoustic and visual features were extracted. Based on them, we used Random Forest classification to identify the most important acoustic and visual features for classifying the tones. The classifiers were trained on produced tone classification (given a set of auditory and visual features, predict the produced tone) and on perceived/responded tone classification (given a set of features, predict the corresponding tone as identified by the participant). The results showed that acoustic features outperformed visual features for tone classification, both for the classification of the produced and the perceived tone. However, tone-naïve perceivers did revert to the use of visual information in certain cases (when they gave wrong responses). So, visual information does not seem to play a significant role in native speakers’ tone production, but tone-naïve perceivers do sometimes consider visual information in their tone identification. These findings provided additional evidence that auditory information is more important than visual information in Mandarin tone perception and tone classification. Notably, visual features contributed to the participants’ erroneous performance. This suggests that visual information actually misled tone-naïve perceivers in their task of tone identification. To some extent, this is consistent with our claim that visual cues do influence tone perception. In addition, the ranking of the auditory features and visual features in tone perception showed that the factor perceiver (i.e., the participant) was responsible for the largest amount of variance explained in the responses by our tone-naïve participants, indicating the importance of individual differences in tone perception. To sum up, perceivers who do not have tone in their language background tend to make use of visual cues from the speakers’ faces for their perception of unknown tones (Mandarin Chinese in this dissertation), in addition to the auditory information they clearly also use. However, auditory cues are still the primary source they rely on. There is a consistent finding across the studies that the variations between tones, speakers and participants have an effect on the accuracy of tone identification for tone-naïve speaker

Neutral Tone in Mandarin: Representation and Interaction with Utterance-level Prosody

In Standard Mandarin, there are syllables that do not carry any of the four citation tones (T1: High-level tone, T2: Mid-rising tone, T3: Low-convex tone and T4: High-falling tone), and they are said to have a neutral tone (NT). These syllables are usually shorter, lighter, prosodically grouped with the preceding CT-bearing syllables. These characteristics of NT have led to a prevailing view that it has no underlying phonological specification. However, research has focused more on how the surface pitch variations of NT are realized rather than the underlying representation of NT. In contrast, morphological, sociolinguistic and diachronic work on NT has suggested that NT may not be a homogeneous entity. In this thesis, I provide acoustic and psycholinguistic evidence that there are two types of NT, Intrinsic NT and Derived NT. Intrinsic NT refers to morphemes that were lexicalized as tone-deleted, unstressed syllables even before the formation of the four CTs of modern Mandarin. Derived NT refers to morphemes derived from the CTs via stress-related tone-deletion. In Part A, the phonological representation of Intrinsic and Derived NT is explored through two production and two processing experiments. The results show that Intrinsic NT is likely to have an underspecified tonal target while Derived NTs are underlyingly CTs. In addition, both subtypes of NT are metrically light, unlike heavy CTs. Part B explores the interaction between NTs and utterance-level prosody in production and perception experiments. NT-bearing syllables have lengthening patterns under focus similar to CT-bearing syllables, in contrast to the realization of unstressed syllables in English. In perception, the identification of intonation (Statement vs. Question) on Intrinsic NT was similar to Derived NT. When compared to CTs, the NTs elicit less bias towards question than T4, and higher accuracy than T2, which may result from their simpler surface representations.CHINA Scholarship COUNCIL (CSC) and Cambridge Trus

Automatic Pronunciation Assessment -- A Review

Pronunciation assessment and its application in computer-aided pronunciation training (CAPT) have seen impressive progress in recent years. With the rapid growth in language processing and deep learning over the past few years, there is a need for an updated review. In this paper, we review methods employed in pronunciation assessment for both phonemic and prosodic. We categorize the main challenges observed in prominent research trends, and highlight existing limitations, and available resources. This is followed by a discussion of the remaining challenges and possible directions for future work.Comment: 9 pages, accepted to EMNLP Finding