The roles of tonal and segmental information in Mandarin spoken word recognition: An eyetracking study

Malins, Jeffrey G.; Joanisse, Marc F.

doi:10.1016/j.jml.2010.02.004

Cited by 92 publications

(121 citation statements)

References 33 publications

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“…Previous research had suggested that segmental and suprasemental information play comparable roles in alphabetic languages such as Spanish, Italian, or Dutch, in which minimal stress pairs are prevalent (Koster, & Cutler, 1997;Soto-Faraco et al, 2001;Tagliapietra & Tabossi, 2005). Given the abundance of minimal tone pairs in Chinese and evidence that segmental and tonal information in Chinese also play comparable roles (e.g., Malins & Joanisse, 2010), we hypothesized that both congruent S+T-and S-T+ trials should elicit significant facilitation on the color naming, in addition to the S+T+ trials. If tonal information is poorly represented in the Chinese mental lexicon, as compared to segmental information (e.g., Taft & Chen, 1992), there should be facilitation in the S+T+ and S+T-trials but not the S-T+ trials.…”

Section: Segments and Lexical Tonesmentioning

confidence: 99%

“…Reliable facilitation was found only when the prime shared both the segment and tone with the target. Moreover, Malins and Joanisse (2010) suggested that tonal and segmental information are accessed concurrently and play comparable roles. Using the eyetracking technique, native Mandarin speakers were asked to select a picture that matched the Chinese word that they heard.…”

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confidence: 99%

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The activation of segmental and tonal information in visual word recognition

Lin

Wang

et al. 2013

Psychon Bull Rev

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Mandarin Chinese has a logographic script in which graphemes map onto syllables and morphemes. It is not clear whether Chinese readers activate phonological information during lexical access, although phonological information is not explicitly represented in Chinese orthography. In the present study, we examined the activation of phonological information, including segmental and tonal information in Chinese visual word recognition, using the Stroop paradigm. Native Mandarin speakers named the presentation color of Chinese characters in Mandarin. The visual stimuli were divided into five types: color characters (e.g., 红, hong2, "red"), homophones of the color characters (S+T+; e.g., 洪, hong2, "flood"), different-tone homophones (S+T-; e.g., 轰, hong1, "boom"), characters that shared the same tone but differed in segments with the color characters (S-T+; e.g., 瓶, ping2, "bottle"), and neutral characters (S-T-; e.g., 牵, qian1, "leading through"). Classic Stroop facilitation was shown in all color-congruent trials, and interference was shown in the incongruent trials. Furthermore, the Stroop effect was stronger for S+T-than for S-T+ trials, and was similar between S+T+ and S+T-trials. These findings suggested that both tonal and segmental forms of information play roles in lexical constraints; however, segmental information has more weight than tonal information. We proposed a revised visual word recognition model in which the functions of both segmental and suprasegmental types of information and their relative weights are taken into account.

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Section: Segments and Lexical Tonesmentioning

confidence: 99%

mentioning

confidence: 99%

The activation of segmental and tonal information in visual word recognition

Lin

Wang

et al. 2013

Psychon Bull Rev

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“…Native speakers of Mandarin may use the tone contour of a word to quickly constrain the activation of lexical candidates that are segmentally identical, but differ in tone (Cutler and Otake, 1999;Cooper et al, 2002;Lee, 2007;Malins and Joanisse, 2010). For instance, Lee (2007) showed that hearing the Mandarin word lou2 (hall) significantly primed responses to the identical target lou2.…”

Section: Introductionmentioning

confidence: 99%

“…Malins and Joanisse (2010) presented Mandarin monolinguals with target images (e.g., chuang2, bed) alongside segmentally unique but tonally overlapping competitors (e.g., niu2, cow). They found that the Mandarin speakers were more likely to fixate the competitors than unrelated distractors, based upon the overlapping tonal information.…”

Section: Introductionmentioning

confidence: 99%

The influence of native-language tones on lexical access in the second language

Shook

Marian

2016

The Journal of the Acoustical Society of America

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When listening to speech in a second language, bilinguals' perception of acoustic-phonetic properties is often influenced by the features that are important in the native language of the bilingual. Furthermore, changes in the perception of segmental contrasts due to L1 experience can influence L2 lexical access during comprehension. The present study investigates whether the effect of L1 experience on L2 processing seen at the segmental level extends to suprasegmental processing. In an eye-tracking task, Mandarin-English bilinguals heard an auditorily presented English word and selected which of two visually presented Chinese characters represented the correct Mandarin translation. The pitch contour of the spoken word was manipulated to either match or mismatch the lexical tone of the Mandarin translation. Results revealed that bilinguals were significantly faster to correctly identify the target and made earlier eye movements to targets when the suprasegmental information of the word spoken in English matched that of its Mandarin translation. The findings provide compelling evidence for bilinguals' sensitivity to suprasegmental tone information, even when listening to a non-tonal language. These results have important implications for the effect of L1 experience on L2 lexical access and language interaction in bilinguals, and are consistent with a highly interactive account of language processing.

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“…Speaker identification and emotional speech recognition systems, as well as speech recognition systems, use different types of speech features which can systematically be divided into segmental and supra-segmental ones [1]. These include traditional features such as linear predictive coefficients, linear prediction cepstral coefficients, mel-frequency cepstral coefficients (MFCC) [2], or unconventional ones like perceptual linear predictive coefficients, log frequency power coefficients [3], gammatone frequency cepstral coefficients [4], or compact multiclass support vector machines [5].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of influence of spectral and prosodic features on GMM classification of Czech and Slovak emotional speech

Přibil

Přibilová²

2013

J AUDIO SPEECH MUSIC PROC.

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This article analyzes and compares influence of different types of spectral and prosodic features for Czech and Slovak emotional speech classification based on Gaussian mixture models (GMM). Influence of initial setting of parameters (number of mixture components and used number of iterations) for GMM training process was analyzed, too. Subsequently, analysis was performed to find how correctness of emotion classification depends on the number and the order of the parameters in the input feature vector and on the computation complexity. Another test was carried out to verify the functionality of the proposed two-level architecture comprising the gender recognizer and of the emotional speech classifier. Next tests were realized to find dependence of some negative aspect (processing of the input speech signal with too short time duration, the gender of a speaker incorrectly determined, etc.) on the stability of the results generated during the GMM classification process. Evaluations and tests were realized with the speech material in the form of sentences of male and female speakers expressing four emotional states (joy, sadness, anger, and a neutral state) in Czech and Slovak languages. In addition, a comparative experiment using the speech data corpus in other language (German) was performed. The mean classification error rate of the whole classifier structure achieves about 21% for all four emotions and both genders, and the best obtained error rate was 3.5% for the sadness style of the female gender. These values are acceptable in this first stage of development of the GMM classifier. On the other hand, the test showed the principal importance of correct classification of the speaker gender in the first level, which has heavy influence on the resulting recognition score of the emotion classification. This GMM classifier should be used for evaluation of the synthetic speech quality after applied voice conversion and emotional speech style transformation.

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The roles of tonal and segmental information in Mandarin spoken word recognition: An eyetracking study

Cited by 92 publications

References 33 publications

The activation of segmental and tonal information in visual word recognition

The activation of segmental and tonal information in visual word recognition

The influence of native-language tones on lexical access in the second language

Evaluation of influence of spectral and prosodic features on GMM classification of Czech and Slovak emotional speech

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