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Journal of the Acoustical Society of America / Volume 131 / Issue 2 / JASA EXPRESS LETTERS

Sine-wave speech recognition in a tonal language

J. Acoust. Soc. Am. Volume 131, Issue 2, pp. EL133-EL138 (2012); (6 pages)

Yan-Mei Feng1, Li Xu2, Ning Zhou3, Guang Yang4, and Shan-Kai Yin4

1Department of Otolaryngology, Shanghai Sixth People’s Hospital, Institute of Otolaryngology, Shanghai Jiao Tong University, Shanghai 200233, People’s Republic of China yanmeifeng2008@gmail.com
2School of Rehabilitation and Communication Sciences, Ohio University, Athens, Ohio 45701 xul@ohio.edu
3Kresge Hearing Research Institute, University of Michigan, Ann Arbor, Michigan 48109 nzhoujo@umich.edu
4Department of Otolaryngology, Shanghai Sixth People’s Hospital, Institute of Otolaryngology, Shanghai Jiao Tong University, Shanghai 200233, People’s Republic of China gyang321@hotmail.com, yinshankai@china.com

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It is hypothesized that in sine-wave replicas of natural speech, lexical tone recognition would be severely impaired due to the loss of F0 information, but the linguistic information at the sentence level could be retrieved even with limited tone information. Forty-one native Mandarin-Chinese-speaking listeners participated in the experiments. Results showed that sine-wave tone-recognition performance was on average only 32.7% correct. However, sine-wave sentence-recognition performance was very accurate, approximately 92% correct on average. Therefore the functional load of lexical tones on sentence recognition is limited, and the high-level recognition of sine-wave sentences is likely attributed to the perceptual organization that is influenced by top-down processes.

© 2012 Acoustical Society of America

Acknowledgments

The research was supported in part by Grant No. 81070778 from NSFC and NIH/NIDCD Grant No. R15-DC009504.

Article Outline

  1. Introduction
  2. Method
  3. Results and discussion

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KEYWORDS and PACS

Keywords

linguistics, natural languages, speech recognition

PACS

  • 43.71.Gv

    Measures of speech perception (intelligibility and quality)

ARTICLE DATA

History
Received 16 Aug 2011
Accepted 10 Nov 2011
Published online 18 Jan 2012
Digital Object Identifier
http://dx.doi.org/10.1121/1.3670594

PUBLICATION DATA

ISSN

0001-4966 (print)  

Publisher

$abstract.society.value is a Member of CrossRef Acoustical Society of America

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Figures (2) Tables (1)

Figures (click on thumbnails to view enlargements)

FIG.1
(Color online) Narrowband spectrograms of the natural speech materials (upper panels) and the sine-wave replicas of the same speech materials (lower panels). The left small panels show the spectrograms of four tone tokens (i.e., /ma1/, /ma2/, /ma3/, and /ma4/) of a male voice. The right panels show the spectrograms of an MHINT sentence (i.e., /wo3 men2 dou1 zai4 xue2 xi2 dian4 nao3 da3 zi4/ or “We are all learning how to type on a computer” in English) of a male voice.

FIG.1 Download High Resolution Image (.zip file) | Export Figure to PowerPoint

FIG.2
Recognition scores of sine-wave Mandarin-Chinese tones and sentences. The three horizontal solid lines of the box represent the 25th percentile, median, and 75th percentile of the data. The whiskers show the range. The filled symbols represent individual data. The dashed line on the left indicates the chance level (i.e., 25% correct) for tone recognition.

FIG.2 Download High Resolution Image (.zip file) | Export Figure to PowerPoint

Tables

Table I. Confusion matrix for the sine-wave tone recognition. Data were pooled across 41 subjects.

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