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Speech Production (SPE-SPRD)

A COMPARATIVE STUDY OF ESTIMATING ARTICULATORY MOVEMENTS FROM PHONEME SEQUENCES AND ACOUSTIC FEATURES


Unlike phoneme sequences, movements of speech articulators (lips, tongue, jaw, velum) and the resultant acoustic signal are known to encode not only the linguistic message but also carry para-linguistic information. While several works exist for estimating articulatory movement from acoustic signals, little is known to what extent articulatory movements can be predicted only from linguistic information, i.e., phoneme sequence.

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Authors:
Abhayjeet Singh, Aravind Illa, Prasanta Kumar Ghosh
Submitted On:
26 May 2020 - 5:45am
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[1] Abhayjeet Singh, Aravind Illa, Prasanta Kumar Ghosh, "A COMPARATIVE STUDY OF ESTIMATING ARTICULATORY MOVEMENTS FROM PHONEME SEQUENCES AND ACOUSTIC FEATURES", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5391. Accessed: Jul. 09, 2020.
@article{5391-20,
url = {http://sigport.org/5391},
author = {Abhayjeet Singh; Aravind Illa; Prasanta Kumar Ghosh },
publisher = {IEEE SigPort},
title = {A COMPARATIVE STUDY OF ESTIMATING ARTICULATORY MOVEMENTS FROM PHONEME SEQUENCES AND ACOUSTIC FEATURES},
year = {2020} }
TY - EJOUR
T1 - A COMPARATIVE STUDY OF ESTIMATING ARTICULATORY MOVEMENTS FROM PHONEME SEQUENCES AND ACOUSTIC FEATURES
AU - Abhayjeet Singh; Aravind Illa; Prasanta Kumar Ghosh
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5391
ER -
Abhayjeet Singh, Aravind Illa, Prasanta Kumar Ghosh. (2020). A COMPARATIVE STUDY OF ESTIMATING ARTICULATORY MOVEMENTS FROM PHONEME SEQUENCES AND ACOUSTIC FEATURES. IEEE SigPort. http://sigport.org/5391
Abhayjeet Singh, Aravind Illa, Prasanta Kumar Ghosh, 2020. A COMPARATIVE STUDY OF ESTIMATING ARTICULATORY MOVEMENTS FROM PHONEME SEQUENCES AND ACOUSTIC FEATURES. Available at: http://sigport.org/5391.
Abhayjeet Singh, Aravind Illa, Prasanta Kumar Ghosh. (2020). "A COMPARATIVE STUDY OF ESTIMATING ARTICULATORY MOVEMENTS FROM PHONEME SEQUENCES AND ACOUSTIC FEATURES." Web.
1. Abhayjeet Singh, Aravind Illa, Prasanta Kumar Ghosh. A COMPARATIVE STUDY OF ESTIMATING ARTICULATORY MOVEMENTS FROM PHONEME SEQUENCES AND ACOUSTIC FEATURES [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5391

SINGLE FREQUENCY FILTER BANK BASED LONG-TERM AVERAGE SPECTRA FOR HYPERNASALITY DETECTION AND ASSESSMENT IN CLEFT LIP AND PALATE SPEECH

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Authors:
Mohammad Hashim Javid, Krishna Gurugubelli, Anil Kumar Vuppala
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14 May 2020 - 2:52am
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SINGLE FREQUENCY FILTER BANK BASED LONG-TERM AVERAGE SPECTRA FOR HYPERNASALITY DETECTION AND ASSESSMENT IN CLEFT LIP AND PALATE SPEECH(1).pdf

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[1] Mohammad Hashim Javid, Krishna Gurugubelli, Anil Kumar Vuppala, "SINGLE FREQUENCY FILTER BANK BASED LONG-TERM AVERAGE SPECTRA FOR HYPERNASALITY DETECTION AND ASSESSMENT IN CLEFT LIP AND PALATE SPEECH", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5239. Accessed: Jul. 09, 2020.
@article{5239-20,
url = {http://sigport.org/5239},
author = {Mohammad Hashim Javid; Krishna Gurugubelli; Anil Kumar Vuppala },
publisher = {IEEE SigPort},
title = {SINGLE FREQUENCY FILTER BANK BASED LONG-TERM AVERAGE SPECTRA FOR HYPERNASALITY DETECTION AND ASSESSMENT IN CLEFT LIP AND PALATE SPEECH},
year = {2020} }
TY - EJOUR
T1 - SINGLE FREQUENCY FILTER BANK BASED LONG-TERM AVERAGE SPECTRA FOR HYPERNASALITY DETECTION AND ASSESSMENT IN CLEFT LIP AND PALATE SPEECH
AU - Mohammad Hashim Javid; Krishna Gurugubelli; Anil Kumar Vuppala
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5239
ER -
Mohammad Hashim Javid, Krishna Gurugubelli, Anil Kumar Vuppala. (2020). SINGLE FREQUENCY FILTER BANK BASED LONG-TERM AVERAGE SPECTRA FOR HYPERNASALITY DETECTION AND ASSESSMENT IN CLEFT LIP AND PALATE SPEECH. IEEE SigPort. http://sigport.org/5239
Mohammad Hashim Javid, Krishna Gurugubelli, Anil Kumar Vuppala, 2020. SINGLE FREQUENCY FILTER BANK BASED LONG-TERM AVERAGE SPECTRA FOR HYPERNASALITY DETECTION AND ASSESSMENT IN CLEFT LIP AND PALATE SPEECH. Available at: http://sigport.org/5239.
Mohammad Hashim Javid, Krishna Gurugubelli, Anil Kumar Vuppala. (2020). "SINGLE FREQUENCY FILTER BANK BASED LONG-TERM AVERAGE SPECTRA FOR HYPERNASALITY DETECTION AND ASSESSMENT IN CLEFT LIP AND PALATE SPEECH." Web.
1. Mohammad Hashim Javid, Krishna Gurugubelli, Anil Kumar Vuppala. SINGLE FREQUENCY FILTER BANK BASED LONG-TERM AVERAGE SPECTRA FOR HYPERNASALITY DETECTION AND ASSESSMENT IN CLEFT LIP AND PALATE SPEECH [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5239

AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET


This paper presents an improved methodology for the segmentation of the Air-Tissue boundaries (ATBs) in the upper airway of the human vocal tract using Real-Time Magnetic Resonance Imaging (rtMRI) videos. Semantic segmentation is deployed in the proposed approach using a Deep learning architecture called SegNet. The network processes an input image to produce a binary output image of the same dimensions having classified each pixel as air cavity or tissue, following which contours are predicted. A Multi-dimensional least square smoothing technique is applied to smoothen the contours.

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Authors:
Valliappan CA, Avinash Kumar, Renuka Mannem, Karthik GR, Prasanta Kumar Ghosh
Submitted On:
8 May 2019 - 6:06am
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[1] Valliappan CA, Avinash Kumar, Renuka Mannem, Karthik GR, Prasanta Kumar Ghosh, "AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4062. Accessed: Jul. 09, 2020.
@article{4062-19,
url = {http://sigport.org/4062},
author = {Valliappan CA; Avinash Kumar; Renuka Mannem; Karthik GR; Prasanta Kumar Ghosh },
publisher = {IEEE SigPort},
title = {AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET},
year = {2019} }
TY - EJOUR
T1 - AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET
AU - Valliappan CA; Avinash Kumar; Renuka Mannem; Karthik GR; Prasanta Kumar Ghosh
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4062
ER -
Valliappan CA, Avinash Kumar, Renuka Mannem, Karthik GR, Prasanta Kumar Ghosh. (2019). AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET. IEEE SigPort. http://sigport.org/4062
Valliappan CA, Avinash Kumar, Renuka Mannem, Karthik GR, Prasanta Kumar Ghosh, 2019. AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET. Available at: http://sigport.org/4062.
Valliappan CA, Avinash Kumar, Renuka Mannem, Karthik GR, Prasanta Kumar Ghosh. (2019). "AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET." Web.
1. Valliappan CA, Avinash Kumar, Renuka Mannem, Karthik GR, Prasanta Kumar Ghosh. AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4062

AIR-TISSUE BOUNDARY SEGMENTATION IN REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING A CONVOLUTIONAL ENCODER-DECODER NETWORK


In this paper, we propose a convolutional encoder-decoder network (CEDN) based approach for upper and lower Air-Tissue Boundary (ATB) segmentation within vocal tract in real-time magnetic resonance imaging (rtMRI) video frames. The output images from CEDN are processed using perimeter and moving average filters to generate smooth contours representing ATBs. Experiments are performed in both seen subject and unseen subject conditions to examine the generalizability of the CEDN based approach.

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Authors:
Renuka Mannem, Prasanta Kumar Ghosh
Submitted On:
8 May 2019 - 5:42am
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main.pdf

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[1] Renuka Mannem, Prasanta Kumar Ghosh, " AIR-TISSUE BOUNDARY SEGMENTATION IN REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING A CONVOLUTIONAL ENCODER-DECODER NETWORK", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4058. Accessed: Jul. 09, 2020.
@article{4058-19,
url = {http://sigport.org/4058},
author = {Renuka Mannem; Prasanta Kumar Ghosh },
publisher = {IEEE SigPort},
title = { AIR-TISSUE BOUNDARY SEGMENTATION IN REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING A CONVOLUTIONAL ENCODER-DECODER NETWORK},
year = {2019} }
TY - EJOUR
T1 - AIR-TISSUE BOUNDARY SEGMENTATION IN REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING A CONVOLUTIONAL ENCODER-DECODER NETWORK
AU - Renuka Mannem; Prasanta Kumar Ghosh
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4058
ER -
Renuka Mannem, Prasanta Kumar Ghosh. (2019). AIR-TISSUE BOUNDARY SEGMENTATION IN REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING A CONVOLUTIONAL ENCODER-DECODER NETWORK. IEEE SigPort. http://sigport.org/4058
Renuka Mannem, Prasanta Kumar Ghosh, 2019. AIR-TISSUE BOUNDARY SEGMENTATION IN REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING A CONVOLUTIONAL ENCODER-DECODER NETWORK. Available at: http://sigport.org/4058.
Renuka Mannem, Prasanta Kumar Ghosh. (2019). " AIR-TISSUE BOUNDARY SEGMENTATION IN REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING A CONVOLUTIONAL ENCODER-DECODER NETWORK." Web.
1. Renuka Mannem, Prasanta Kumar Ghosh. AIR-TISSUE BOUNDARY SEGMENTATION IN REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING A CONVOLUTIONAL ENCODER-DECODER NETWORK [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4058

Representation learning using convolution neural network for acoustic-to-articulatory inversion

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Authors:
Aravind Illa, Prasanta Kumar Ghosh
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4 May 2019 - 8:15am
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E2E_AAI_ICASSP_19.pdf

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[1] Aravind Illa, Prasanta Kumar Ghosh, "Representation learning using convolution neural network for acoustic-to-articulatory inversion", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3907. Accessed: Jul. 09, 2020.
@article{3907-19,
url = {http://sigport.org/3907},
author = {Aravind Illa; Prasanta Kumar Ghosh },
publisher = {IEEE SigPort},
title = {Representation learning using convolution neural network for acoustic-to-articulatory inversion},
year = {2019} }
TY - EJOUR
T1 - Representation learning using convolution neural network for acoustic-to-articulatory inversion
AU - Aravind Illa; Prasanta Kumar Ghosh
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3907
ER -
Aravind Illa, Prasanta Kumar Ghosh. (2019). Representation learning using convolution neural network for acoustic-to-articulatory inversion. IEEE SigPort. http://sigport.org/3907
Aravind Illa, Prasanta Kumar Ghosh, 2019. Representation learning using convolution neural network for acoustic-to-articulatory inversion. Available at: http://sigport.org/3907.
Aravind Illa, Prasanta Kumar Ghosh. (2019). "Representation learning using convolution neural network for acoustic-to-articulatory inversion." Web.
1. Aravind Illa, Prasanta Kumar Ghosh. Representation learning using convolution neural network for acoustic-to-articulatory inversion [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3907

Voice Impersonation Using Generative Adversarial Networks

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Authors:
Rita Singh, Bhiksha Raj
Submitted On:
14 April 2018 - 8:39pm
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[1] Rita Singh, Bhiksha Raj, "Voice Impersonation Using Generative Adversarial Networks", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2862. Accessed: Jul. 09, 2020.
@article{2862-18,
url = {http://sigport.org/2862},
author = {Rita Singh; Bhiksha Raj },
publisher = {IEEE SigPort},
title = {Voice Impersonation Using Generative Adversarial Networks},
year = {2018} }
TY - EJOUR
T1 - Voice Impersonation Using Generative Adversarial Networks
AU - Rita Singh; Bhiksha Raj
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2862
ER -
Rita Singh, Bhiksha Raj. (2018). Voice Impersonation Using Generative Adversarial Networks. IEEE SigPort. http://sigport.org/2862
Rita Singh, Bhiksha Raj, 2018. Voice Impersonation Using Generative Adversarial Networks. Available at: http://sigport.org/2862.
Rita Singh, Bhiksha Raj. (2018). "Voice Impersonation Using Generative Adversarial Networks." Web.
1. Rita Singh, Bhiksha Raj. Voice Impersonation Using Generative Adversarial Networks [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2862

Voice Impersonation Using Generative Adversarial Networks

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Authors:
Rita Singh, Bhiksha Raj
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14 April 2018 - 8:39pm
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[1] Rita Singh, Bhiksha Raj, "Voice Impersonation Using Generative Adversarial Networks", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2861. Accessed: Jul. 09, 2020.
@article{2861-18,
url = {http://sigport.org/2861},
author = {Rita Singh; Bhiksha Raj },
publisher = {IEEE SigPort},
title = {Voice Impersonation Using Generative Adversarial Networks},
year = {2018} }
TY - EJOUR
T1 - Voice Impersonation Using Generative Adversarial Networks
AU - Rita Singh; Bhiksha Raj
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2861
ER -
Rita Singh, Bhiksha Raj. (2018). Voice Impersonation Using Generative Adversarial Networks. IEEE SigPort. http://sigport.org/2861
Rita Singh, Bhiksha Raj, 2018. Voice Impersonation Using Generative Adversarial Networks. Available at: http://sigport.org/2861.
Rita Singh, Bhiksha Raj. (2018). "Voice Impersonation Using Generative Adversarial Networks." Web.
1. Rita Singh, Bhiksha Raj. Voice Impersonation Using Generative Adversarial Networks [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2861

DIRECT, NEAR REAL TIME ANIMATION OF A 3D TONGUE MODEL USING NON-INVASIVE ULTRASOUND IMAGES


A new technique for representing speech articulation with
an ultrasound-driven finite element model of the tongue is
presented. By using a snake contour extraction algorithm
with anatomically motivated constraints and a common
coordinate system between the ultrasound and the tongue
model, it is possible for the first time to obtain a realistic 3D
simulation of the tongue directly from a non-invasive sensor
(ultrasound), without mapping through any intermediate
sensor modalities, and at near real-time frame rates.

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19 April 2018 - 9:35pm
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[1] , "DIRECT, NEAR REAL TIME ANIMATION OF A 3D TONGUE MODEL USING NON-INVASIVE ULTRASOUND IMAGES", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2846. Accessed: Jul. 09, 2020.
@article{2846-18,
url = {http://sigport.org/2846},
author = { },
publisher = {IEEE SigPort},
title = {DIRECT, NEAR REAL TIME ANIMATION OF A 3D TONGUE MODEL USING NON-INVASIVE ULTRASOUND IMAGES},
year = {2018} }
TY - EJOUR
T1 - DIRECT, NEAR REAL TIME ANIMATION OF A 3D TONGUE MODEL USING NON-INVASIVE ULTRASOUND IMAGES
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2846
ER -
. (2018). DIRECT, NEAR REAL TIME ANIMATION OF A 3D TONGUE MODEL USING NON-INVASIVE ULTRASOUND IMAGES. IEEE SigPort. http://sigport.org/2846
, 2018. DIRECT, NEAR REAL TIME ANIMATION OF A 3D TONGUE MODEL USING NON-INVASIVE ULTRASOUND IMAGES. Available at: http://sigport.org/2846.
. (2018). "DIRECT, NEAR REAL TIME ANIMATION OF A 3D TONGUE MODEL USING NON-INVASIVE ULTRASOUND IMAGES." Web.
1. . DIRECT, NEAR REAL TIME ANIMATION OF A 3D TONGUE MODEL USING NON-INVASIVE ULTRASOUND IMAGES [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2846

Production and Perception of Focus in L2 Mandarin of Qiang Speakers


The present study investigated production and perception of focus in L2 Mandarin of Qiang speakers. Three target sentences were uttered under four focus conditions, i.e., initial, medial, final and neutral focus by 10 Qiang-Mandarin speakers. Systematic acoustic analysis showed that: (1) In Qiang-Mandarin, on-focus words exhibit significant F0 rising, intensity increasing and duration lengthening. There is no Post-focus Compression (PFC). The duration of pre-focus and post-focus words remains largely intact.

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Authors:
Bei Wang
Submitted On:
15 October 2016 - 5:27am
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[1] Bei Wang, "Production and Perception of Focus in L2 Mandarin of Qiang Speakers", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1224. Accessed: Jul. 09, 2020.
@article{1224-16,
url = {http://sigport.org/1224},
author = {Bei Wang },
publisher = {IEEE SigPort},
title = {Production and Perception of Focus in L2 Mandarin of Qiang Speakers},
year = {2016} }
TY - EJOUR
T1 - Production and Perception of Focus in L2 Mandarin of Qiang Speakers
AU - Bei Wang
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1224
ER -
Bei Wang. (2016). Production and Perception of Focus in L2 Mandarin of Qiang Speakers. IEEE SigPort. http://sigport.org/1224
Bei Wang, 2016. Production and Perception of Focus in L2 Mandarin of Qiang Speakers. Available at: http://sigport.org/1224.
Bei Wang. (2016). "Production and Perception of Focus in L2 Mandarin of Qiang Speakers." Web.
1. Bei Wang. Production and Perception of Focus in L2 Mandarin of Qiang Speakers [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1224

An Interface Research on Rhetorical Structure and Prosody Features in Chinese Reading Texts


This paper conducted an interface research on rhetorical and prosodic aspects of Chinese reading discourses within the Rhetorical Structure Theory (RST) framework. Ten discourses in 3 genres (Commentary, Narrative, and Descriptive) from the Annotated Speech Corpus of Chinese Discourse (ASCCD) were diagrammed in RST. The recordings from 5 males and 5 females were annotated and further analyzed acoustically and statistically by applying Praat and R.

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Authors:
Liang Zhang, Yuan Jia, Aijun Li
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18 October 2016 - 7:52am
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Liang_O10-4-1016.pptx

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[1] Liang Zhang, Yuan Jia, Aijun Li, "An Interface Research on Rhetorical Structure and Prosody Features in Chinese Reading Texts", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1217. Accessed: Jul. 09, 2020.
@article{1217-16,
url = {http://sigport.org/1217},
author = {Liang Zhang; Yuan Jia; Aijun Li },
publisher = {IEEE SigPort},
title = {An Interface Research on Rhetorical Structure and Prosody Features in Chinese Reading Texts},
year = {2016} }
TY - EJOUR
T1 - An Interface Research on Rhetorical Structure and Prosody Features in Chinese Reading Texts
AU - Liang Zhang; Yuan Jia; Aijun Li
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1217
ER -
Liang Zhang, Yuan Jia, Aijun Li. (2016). An Interface Research on Rhetorical Structure and Prosody Features in Chinese Reading Texts. IEEE SigPort. http://sigport.org/1217
Liang Zhang, Yuan Jia, Aijun Li, 2016. An Interface Research on Rhetorical Structure and Prosody Features in Chinese Reading Texts. Available at: http://sigport.org/1217.
Liang Zhang, Yuan Jia, Aijun Li. (2016). "An Interface Research on Rhetorical Structure and Prosody Features in Chinese Reading Texts." Web.
1. Liang Zhang, Yuan Jia, Aijun Li. An Interface Research on Rhetorical Structure and Prosody Features in Chinese Reading Texts [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1217

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