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ISCSLP 2016

ISCSLP 2016

Welcome to ISCSLP 2016 - October 17-20, 2016, Tianjin, China

The ISCSLP will be hosted by Tianjin University. Tianjin has a reputation throughout China for being extremely friendly, safe and a place of delicious food. Welcome to Tianjin to attend the ISCSLP2016. The 10th International Symposium on Chinese Spoken Language Processing (ISCSLP 2016) will be held on October 17-20, 2016 in Tianjin. ISCSLP is a biennial conference for scientists, researchers, and practitioners to report and discuss the latest progress in all theoretical and technological aspects of spoken language processing. While the ISCSLP is focused primarily on Chinese languages, works on other languages that may be applied to Chinese speech and language are also encouraged. The working language of ISCSLP is English.

 

Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment


This study investigates how automatic scorings based on speech technology can affect human raters' judgement of students' oral language proficiency in L2 speaking tests. Automatic scorings based on ASR are widely used in non-critical speaking tests or practices and relatively high correlations between machine scores and human scores have been reported. In high-stakes speaking tests, however, many teachers remain skeptical about the fairness of automatic scores given by machines even with the most advanced scoring methods.

Paper Details

Authors:
Dean Luo, Wentao Gu, Ruxin Luo, Lixin Wang
Submitted On:
16 October 2016 - 11:17pm
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Paper.No_.25.pptx

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[1] Dean Luo, Wentao Gu, Ruxin Luo, Lixin Wang, "Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1210. Accessed: Jul. 21, 2018.
@article{1210-16,
url = {http://sigport.org/1210},
author = {Dean Luo; Wentao Gu; Ruxin Luo; Lixin Wang },
publisher = {IEEE SigPort},
title = {Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment},
year = {2016} }
TY - EJOUR
T1 - Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment
AU - Dean Luo; Wentao Gu; Ruxin Luo; Lixin Wang
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1210
ER -
Dean Luo, Wentao Gu, Ruxin Luo, Lixin Wang. (2016). Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment. IEEE SigPort. http://sigport.org/1210
Dean Luo, Wentao Gu, Ruxin Luo, Lixin Wang, 2016. Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment. Available at: http://sigport.org/1210.
Dean Luo, Wentao Gu, Ruxin Luo, Lixin Wang. (2016). "Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment." Web.
1. Dean Luo, Wentao Gu, Ruxin Luo, Lixin Wang. Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1210

Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment


This study investigates how automatic scorings based on speech technology can affect human raters' judgement of students' oral language proficiency in L2 speaking tests. Automatic scorings based on ASR are widely used in non-critical speaking tests or practices and relatively high correlations between machine scores and human scores have been reported. In high-stakes speaking tests, however, many teachers remain skeptical about the fairness of automatic scores given by machines even with the most advanced scoring methods.

Paper Details

Authors:
Dean Luo, Wentao Gu, Ruxin Luo, Lixin Wang
Submitted On:
14 October 2016 - 12:37pm
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Paper.No_.25.pptx

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[1] Dean Luo, Wentao Gu, Ruxin Luo, Lixin Wang, "Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1209. Accessed: Jul. 21, 2018.
@article{1209-16,
url = {http://sigport.org/1209},
author = {Dean Luo; Wentao Gu; Ruxin Luo; Lixin Wang },
publisher = {IEEE SigPort},
title = {Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment},
year = {2016} }
TY - EJOUR
T1 - Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment
AU - Dean Luo; Wentao Gu; Ruxin Luo; Lixin Wang
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1209
ER -
Dean Luo, Wentao Gu, Ruxin Luo, Lixin Wang. (2016). Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment. IEEE SigPort. http://sigport.org/1209
Dean Luo, Wentao Gu, Ruxin Luo, Lixin Wang, 2016. Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment. Available at: http://sigport.org/1209.
Dean Luo, Wentao Gu, Ruxin Luo, Lixin Wang. (2016). "Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment." Web.
1. Dean Luo, Wentao Gu, Ruxin Luo, Lixin Wang. Investigation of the Effects of Automatic Scoring Technology on Human Raters' Performances in L2 Speech Proficiency Assessment [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1209

Rapid Speaker Adaptation Based on D-code Extracted from BLSTM-RNN in LVCSR


Recently, several fast speaker adaptation methods have been proposed for the hybrid DNN-HMM models based on the so called discriminative speaker codes (SC) and applied to unsupervised speaker adaptation in speech recognition. It has been demonstrated that the SC based methods are quite effective in adapting DNNs even when only a very small amount of adaptation data is available. However, in this way we have to estimate speaker code for new speakers by an updating process and obtain the final results through two-pass decoding.

Paper Details

Authors:
Shaofei Xue, Zhijie Yan, Zhiying Huang, Lirong Dai
Submitted On:
14 October 2016 - 12:31pm
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Rapid Speaker Adaptation Based on D-code Extracted from BLSTM-RNN in LVCSR.pdf

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[1] Shaofei Xue, Zhijie Yan, Zhiying Huang, Lirong Dai, "Rapid Speaker Adaptation Based on D-code Extracted from BLSTM-RNN in LVCSR", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1208. Accessed: Jul. 21, 2018.
@article{1208-16,
url = {http://sigport.org/1208},
author = {Shaofei Xue; Zhijie Yan; Zhiying Huang; Lirong Dai },
publisher = {IEEE SigPort},
title = {Rapid Speaker Adaptation Based on D-code Extracted from BLSTM-RNN in LVCSR},
year = {2016} }
TY - EJOUR
T1 - Rapid Speaker Adaptation Based on D-code Extracted from BLSTM-RNN in LVCSR
AU - Shaofei Xue; Zhijie Yan; Zhiying Huang; Lirong Dai
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1208
ER -
Shaofei Xue, Zhijie Yan, Zhiying Huang, Lirong Dai. (2016). Rapid Speaker Adaptation Based on D-code Extracted from BLSTM-RNN in LVCSR. IEEE SigPort. http://sigport.org/1208
Shaofei Xue, Zhijie Yan, Zhiying Huang, Lirong Dai, 2016. Rapid Speaker Adaptation Based on D-code Extracted from BLSTM-RNN in LVCSR. Available at: http://sigport.org/1208.
Shaofei Xue, Zhijie Yan, Zhiying Huang, Lirong Dai. (2016). "Rapid Speaker Adaptation Based on D-code Extracted from BLSTM-RNN in LVCSR." Web.
1. Shaofei Xue, Zhijie Yan, Zhiying Huang, Lirong Dai. Rapid Speaker Adaptation Based on D-code Extracted from BLSTM-RNN in LVCSR [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1208

A REGRESSION APPROACH TO BINAURAL SPEECH SEGREGATION VIA DEEP NEURAL NETWORK


This paper proposes a novel regression approach to binaural speech segregation based on deep neural network (DNN). In contrast to the conventional ideal binary mask (IBM) method using DNN with the interaural time difference (ITD) and interaural level difference (ILD) as the auditory features, the log-power spectra (LPS) features of target speech are directly predicted via a regression DNN model by concatenating the monaural LPS features and the binaural features as the input.

Paper Details

Authors:
Nana Fan, Jun Du, Lirong Dai
Submitted On:
14 October 2016 - 11:07pm
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oral-presentation3.pptx

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oral-presentation3.pptx

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Keywords

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[1] Nana Fan, Jun Du, Lirong Dai, "A REGRESSION APPROACH TO BINAURAL SPEECH SEGREGATION VIA DEEP NEURAL NETWORK", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1207. Accessed: Jul. 21, 2018.
@article{1207-16,
url = {http://sigport.org/1207},
author = {Nana Fan; Jun Du; Lirong Dai },
publisher = {IEEE SigPort},
title = {A REGRESSION APPROACH TO BINAURAL SPEECH SEGREGATION VIA DEEP NEURAL NETWORK},
year = {2016} }
TY - EJOUR
T1 - A REGRESSION APPROACH TO BINAURAL SPEECH SEGREGATION VIA DEEP NEURAL NETWORK
AU - Nana Fan; Jun Du; Lirong Dai
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1207
ER -
Nana Fan, Jun Du, Lirong Dai. (2016). A REGRESSION APPROACH TO BINAURAL SPEECH SEGREGATION VIA DEEP NEURAL NETWORK. IEEE SigPort. http://sigport.org/1207
Nana Fan, Jun Du, Lirong Dai, 2016. A REGRESSION APPROACH TO BINAURAL SPEECH SEGREGATION VIA DEEP NEURAL NETWORK. Available at: http://sigport.org/1207.
Nana Fan, Jun Du, Lirong Dai. (2016). "A REGRESSION APPROACH TO BINAURAL SPEECH SEGREGATION VIA DEEP NEURAL NETWORK." Web.
1. Nana Fan, Jun Du, Lirong Dai. A REGRESSION APPROACH TO BINAURAL SPEECH SEGREGATION VIA DEEP NEURAL NETWORK [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1207

Digit-dependent Local I-Vector for Text-Prompted Speaker Verification with


The widely adopted i-vector performances well in textindependent speaker verification with long speech duration.

Paper Details

Authors:
Peixin Chen, Wu Guo, Guoping Hu
Submitted On:
14 October 2016 - 10:24pm
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ISCSLP2016_PeixinChen.pdf

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[1] Peixin Chen, Wu Guo, Guoping Hu, "Digit-dependent Local I-Vector for Text-Prompted Speaker Verification with", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1206. Accessed: Jul. 21, 2018.
@article{1206-16,
url = {http://sigport.org/1206},
author = {Peixin Chen; Wu Guo; Guoping Hu },
publisher = {IEEE SigPort},
title = {Digit-dependent Local I-Vector for Text-Prompted Speaker Verification with},
year = {2016} }
TY - EJOUR
T1 - Digit-dependent Local I-Vector for Text-Prompted Speaker Verification with
AU - Peixin Chen; Wu Guo; Guoping Hu
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1206
ER -
Peixin Chen, Wu Guo, Guoping Hu. (2016). Digit-dependent Local I-Vector for Text-Prompted Speaker Verification with. IEEE SigPort. http://sigport.org/1206
Peixin Chen, Wu Guo, Guoping Hu, 2016. Digit-dependent Local I-Vector for Text-Prompted Speaker Verification with. Available at: http://sigport.org/1206.
Peixin Chen, Wu Guo, Guoping Hu. (2016). "Digit-dependent Local I-Vector for Text-Prompted Speaker Verification with." Web.
1. Peixin Chen, Wu Guo, Guoping Hu. Digit-dependent Local I-Vector for Text-Prompted Speaker Verification with [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1206

Exploring Tonal Information for Lhasa Dialect Acoustic Modeling


Detailed analysis of tonal features for Tibetan Lhasa dialect is an important task for Tibetan automatic speech recognition (ASR) applications. However, it is difficult to utilize tonal information because it remains controversial how many tonal patterns the Lhasa dialect has. Therefore, few studies have focused on modeling the tonal information of the Lhasa dialect for speech recognition purpose. For this reason, we investigated influences of the tonal information on the performance of Lhasa Tibetan speech recognition.

Paper Details

Authors:
Jian Li, Hongcui Wang, Longbiao Wang, Jianwu Dang, Kuntharrgyal khuru, Gyaltsen Lobsang
Submitted On:
14 October 2016 - 11:52am
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Exploring Tonal Information for Lhasa Dialect Acoustic Modeling

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[1] Jian Li, Hongcui Wang, Longbiao Wang, Jianwu Dang, Kuntharrgyal khuru, Gyaltsen Lobsang, "Exploring Tonal Information for Lhasa Dialect Acoustic Modeling", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1205. Accessed: Jul. 21, 2018.
@article{1205-16,
url = {http://sigport.org/1205},
author = {Jian Li; Hongcui Wang; Longbiao Wang; Jianwu Dang; Kuntharrgyal khuru; Gyaltsen Lobsang },
publisher = {IEEE SigPort},
title = {Exploring Tonal Information for Lhasa Dialect Acoustic Modeling},
year = {2016} }
TY - EJOUR
T1 - Exploring Tonal Information for Lhasa Dialect Acoustic Modeling
AU - Jian Li; Hongcui Wang; Longbiao Wang; Jianwu Dang; Kuntharrgyal khuru; Gyaltsen Lobsang
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1205
ER -
Jian Li, Hongcui Wang, Longbiao Wang, Jianwu Dang, Kuntharrgyal khuru, Gyaltsen Lobsang. (2016). Exploring Tonal Information for Lhasa Dialect Acoustic Modeling. IEEE SigPort. http://sigport.org/1205
Jian Li, Hongcui Wang, Longbiao Wang, Jianwu Dang, Kuntharrgyal khuru, Gyaltsen Lobsang, 2016. Exploring Tonal Information for Lhasa Dialect Acoustic Modeling. Available at: http://sigport.org/1205.
Jian Li, Hongcui Wang, Longbiao Wang, Jianwu Dang, Kuntharrgyal khuru, Gyaltsen Lobsang. (2016). "Exploring Tonal Information for Lhasa Dialect Acoustic Modeling." Web.
1. Jian Li, Hongcui Wang, Longbiao Wang, Jianwu Dang, Kuntharrgyal khuru, Gyaltsen Lobsang. Exploring Tonal Information for Lhasa Dialect Acoustic Modeling [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1205

The Design and Implementation of HMM-based Dai Speech Synthesis


By far there are more than 1.2 million Dai compatriots using Dai language in Yunnan province,researching Dai speech synthesis has great significance in advancing the informationization of Dai.This paper researches the implementation of Dai speech synthesis by taking the HMM speech synthesis framework and STRAIGHT synthesizer into account.
In this paper,collection and selection of Dai text corpus,recording of speech corpus,text normalization,segmentation,Romanization and the implementation of acoustic model training are described.

Paper Details

Authors:
Wang Zhan,Yang Jian,Yang xin
Submitted On:
14 October 2016 - 11:30am
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会议海报.pdf

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[1] Wang Zhan,Yang Jian,Yang xin, "The Design and Implementation of HMM-based Dai Speech Synthesis", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1204. Accessed: Jul. 21, 2018.
@article{1204-16,
url = {http://sigport.org/1204},
author = {Wang Zhan;Yang Jian;Yang xin },
publisher = {IEEE SigPort},
title = {The Design and Implementation of HMM-based Dai Speech Synthesis},
year = {2016} }
TY - EJOUR
T1 - The Design and Implementation of HMM-based Dai Speech Synthesis
AU - Wang Zhan;Yang Jian;Yang xin
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1204
ER -
Wang Zhan,Yang Jian,Yang xin. (2016). The Design and Implementation of HMM-based Dai Speech Synthesis. IEEE SigPort. http://sigport.org/1204
Wang Zhan,Yang Jian,Yang xin, 2016. The Design and Implementation of HMM-based Dai Speech Synthesis. Available at: http://sigport.org/1204.
Wang Zhan,Yang Jian,Yang xin. (2016). "The Design and Implementation of HMM-based Dai Speech Synthesis." Web.
1. Wang Zhan,Yang Jian,Yang xin. The Design and Implementation of HMM-based Dai Speech Synthesis [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1204

Contributions of the Piriform Fossa of Female Speakers to Vowel Spectra


The bilateral cavities of the piriform fossa are the side branches of the vocal tract and produce anti-resonance(s) in the transfer function. This effect has been known for male vocal tracts, but female data were few. This study investigates contributions of the piriform fossa to vowel spectra in female vocal tracts by means of MRI-based vocal-tract modeling and acoustic experiment with the water-filling technique. Results from three female subjects indicate that the piriform fossa generates one or two dips in the frequency region of 4-6 kHz.

Paper Details

Authors:
Congcong Zhang, Kiyoshi Honda, Ju Zhang, Jianguo Wei
Submitted On:
15 October 2016 - 12:24am
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zcc_ISCSLP2016.pdf

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[1] Congcong Zhang, Kiyoshi Honda, Ju Zhang, Jianguo Wei, "Contributions of the Piriform Fossa of Female Speakers to Vowel Spectra", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1203. Accessed: Jul. 21, 2018.
@article{1203-16,
url = {http://sigport.org/1203},
author = {Congcong Zhang; Kiyoshi Honda; Ju Zhang; Jianguo Wei },
publisher = {IEEE SigPort},
title = {Contributions of the Piriform Fossa of Female Speakers to Vowel Spectra},
year = {2016} }
TY - EJOUR
T1 - Contributions of the Piriform Fossa of Female Speakers to Vowel Spectra
AU - Congcong Zhang; Kiyoshi Honda; Ju Zhang; Jianguo Wei
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1203
ER -
Congcong Zhang, Kiyoshi Honda, Ju Zhang, Jianguo Wei. (2016). Contributions of the Piriform Fossa of Female Speakers to Vowel Spectra. IEEE SigPort. http://sigport.org/1203
Congcong Zhang, Kiyoshi Honda, Ju Zhang, Jianguo Wei, 2016. Contributions of the Piriform Fossa of Female Speakers to Vowel Spectra. Available at: http://sigport.org/1203.
Congcong Zhang, Kiyoshi Honda, Ju Zhang, Jianguo Wei. (2016). "Contributions of the Piriform Fossa of Female Speakers to Vowel Spectra." Web.
1. Congcong Zhang, Kiyoshi Honda, Ju Zhang, Jianguo Wei. Contributions of the Piriform Fossa of Female Speakers to Vowel Spectra [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1203

Individual difference and acoustic effect of female laryngeal cavities


This study examines the acoustic effect of the laryngeal cavity of female speakers on the higher vowel spectra. To do so, MRI data of vowels /a/ and /i/ obtained from three female speakers were analyzed with data from a male speaker as reference. 3D vocal-tract shapes were extracted from the MRI data and printed as solid mechanical models. Transfer functions of the models' vocal tracts were estimated by a transmission line model. Individual variations of the laryngeal cavity were described by the area functions of the cavity.

Paper Details

Authors:
Jing Li, Kiyoshi Honda, Ju Zhang, Jianguo Wei
Submitted On:
14 October 2016 - 10:43am
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[ISCSLP2016] ID82 Oral.PDF

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[1] Jing Li, Kiyoshi Honda, Ju Zhang, Jianguo Wei, "Individual difference and acoustic effect of female laryngeal cavities", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1202. Accessed: Jul. 21, 2018.
@article{1202-16,
url = {http://sigport.org/1202},
author = {Jing Li; Kiyoshi Honda; Ju Zhang; Jianguo Wei },
publisher = {IEEE SigPort},
title = {Individual difference and acoustic effect of female laryngeal cavities},
year = {2016} }
TY - EJOUR
T1 - Individual difference and acoustic effect of female laryngeal cavities
AU - Jing Li; Kiyoshi Honda; Ju Zhang; Jianguo Wei
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1202
ER -
Jing Li, Kiyoshi Honda, Ju Zhang, Jianguo Wei. (2016). Individual difference and acoustic effect of female laryngeal cavities. IEEE SigPort. http://sigport.org/1202
Jing Li, Kiyoshi Honda, Ju Zhang, Jianguo Wei, 2016. Individual difference and acoustic effect of female laryngeal cavities. Available at: http://sigport.org/1202.
Jing Li, Kiyoshi Honda, Ju Zhang, Jianguo Wei. (2016). "Individual difference and acoustic effect of female laryngeal cavities." Web.
1. Jing Li, Kiyoshi Honda, Ju Zhang, Jianguo Wei. Individual difference and acoustic effect of female laryngeal cavities [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1202

Cognitive Representation of Phonological Categories: The Evidence from Mandarin Speakers’ Learning of Cantonese Tones

Paper Details

Authors:
Kaile Zhang, Yonghong Li, Gang Peng
Submitted On:
14 October 2016 - 10:42am
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ISCSLP_136_Kaile.pdf

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[1] Kaile Zhang, Yonghong Li, Gang Peng, "Cognitive Representation of Phonological Categories: The Evidence from Mandarin Speakers’ Learning of Cantonese Tones", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1201. Accessed: Jul. 21, 2018.
@article{1201-16,
url = {http://sigport.org/1201},
author = {Kaile Zhang; Yonghong Li; Gang Peng },
publisher = {IEEE SigPort},
title = {Cognitive Representation of Phonological Categories: The Evidence from Mandarin Speakers’ Learning of Cantonese Tones},
year = {2016} }
TY - EJOUR
T1 - Cognitive Representation of Phonological Categories: The Evidence from Mandarin Speakers’ Learning of Cantonese Tones
AU - Kaile Zhang; Yonghong Li; Gang Peng
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1201
ER -
Kaile Zhang, Yonghong Li, Gang Peng. (2016). Cognitive Representation of Phonological Categories: The Evidence from Mandarin Speakers’ Learning of Cantonese Tones. IEEE SigPort. http://sigport.org/1201
Kaile Zhang, Yonghong Li, Gang Peng, 2016. Cognitive Representation of Phonological Categories: The Evidence from Mandarin Speakers’ Learning of Cantonese Tones. Available at: http://sigport.org/1201.
Kaile Zhang, Yonghong Li, Gang Peng. (2016). "Cognitive Representation of Phonological Categories: The Evidence from Mandarin Speakers’ Learning of Cantonese Tones." Web.
1. Kaile Zhang, Yonghong Li, Gang Peng. Cognitive Representation of Phonological Categories: The Evidence from Mandarin Speakers’ Learning of Cantonese Tones [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1201

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