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Audio and Acoustic Signal Processing

Action Classification from Motion Capture Data using Topological Data Analysis


This paper proposes a novel framework for activity recognition from 3D motion capture data using topological data analysis (TDA). We extract point clouds describing the oscillatory patterns of body joints from the principal components of their time series using Taken's delay embedding. Topological persistence from TDA is exploited to extract topological invariants of the constructed point clouds. We propose a feature extraction method from persistence diagrams in order to generate robust low dimensional features used for classification of different activities.

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Authors:
Alireza Dirafzoon, Namita Lokare and Edgar Lobaton
Submitted On:
26 November 2016 - 11:07am
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Poster

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Presentation

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[1] Alireza Dirafzoon, Namita Lokare and Edgar Lobaton, "Action Classification from Motion Capture Data using Topological Data Analysis", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1310. Accessed: Oct. 19, 2017.
@article{1310-16,
url = {http://sigport.org/1310},
author = {Alireza Dirafzoon; Namita Lokare and Edgar Lobaton },
publisher = {IEEE SigPort},
title = {Action Classification from Motion Capture Data using Topological Data Analysis},
year = {2016} }
TY - EJOUR
T1 - Action Classification from Motion Capture Data using Topological Data Analysis
AU - Alireza Dirafzoon; Namita Lokare and Edgar Lobaton
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1310
ER -
Alireza Dirafzoon, Namita Lokare and Edgar Lobaton. (2016). Action Classification from Motion Capture Data using Topological Data Analysis. IEEE SigPort. http://sigport.org/1310
Alireza Dirafzoon, Namita Lokare and Edgar Lobaton, 2016. Action Classification from Motion Capture Data using Topological Data Analysis. Available at: http://sigport.org/1310.
Alireza Dirafzoon, Namita Lokare and Edgar Lobaton. (2016). "Action Classification from Motion Capture Data using Topological Data Analysis." Web.
1. Alireza Dirafzoon, Namita Lokare and Edgar Lobaton. Action Classification from Motion Capture Data using Topological Data Analysis [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1310

Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery


In this paper we propose a hierarchical activity clustering methodology which incorporates the use of topological persistence analysis. Our clustering methodology captures the hierarchies present in the data and is therefore able to show the dependencies that exist between these activities. We make use of an aggregate persistence diagram to select robust graphical structures present within the dataset. These models are stable over a bound and provide accurate classification results.

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Authors:
Namita Lokare, Daniel Benavides, Sahil Juneja, Edgar Lobaton
Submitted On:
26 November 2016 - 11:17am
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Poster

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Presentation

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[1] Namita Lokare, Daniel Benavides, Sahil Juneja, Edgar Lobaton, "Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1309. Accessed: Oct. 19, 2017.
@article{1309-16,
url = {http://sigport.org/1309},
author = {Namita Lokare; Daniel Benavides; Sahil Juneja; Edgar Lobaton },
publisher = {IEEE SigPort},
title = {Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery},
year = {2016} }
TY - EJOUR
T1 - Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery
AU - Namita Lokare; Daniel Benavides; Sahil Juneja; Edgar Lobaton
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1309
ER -
Namita Lokare, Daniel Benavides, Sahil Juneja, Edgar Lobaton. (2016). Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery. IEEE SigPort. http://sigport.org/1309
Namita Lokare, Daniel Benavides, Sahil Juneja, Edgar Lobaton, 2016. Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery. Available at: http://sigport.org/1309.
Namita Lokare, Daniel Benavides, Sahil Juneja, Edgar Lobaton. (2016). "Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery." Web.
1. Namita Lokare, Daniel Benavides, Sahil Juneja, Edgar Lobaton. Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1309

Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia


The absence of manually annotated training data presents an obstacle for the development of machine-learning based NLP tools in Indonesia. Existing annotation tools lack a mobile-friendly interface which is a problem in Indonesia where most users access the internet using their smartphone. In this paper we propose the first mobile collaborative data annotation tool and evaluate it in an experiment involving 15 Indonesian students who annotated 1500 data records using their smartphones. Users confirmed

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Authors:
Lisa Madlberger, Ayu Purwarianti
Submitted On:
21 November 2016 - 10:49pm
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presentation_IALP2016_46.pdf

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[1] Lisa Madlberger, Ayu Purwarianti, "Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia ", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1290. Accessed: Oct. 19, 2017.
@article{1290-16,
url = {http://sigport.org/1290},
author = {Lisa Madlberger; Ayu Purwarianti },
publisher = {IEEE SigPort},
title = {Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia },
year = {2016} }
TY - EJOUR
T1 - Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia
AU - Lisa Madlberger; Ayu Purwarianti
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1290
ER -
Lisa Madlberger, Ayu Purwarianti. (2016). Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia . IEEE SigPort. http://sigport.org/1290
Lisa Madlberger, Ayu Purwarianti, 2016. Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia . Available at: http://sigport.org/1290.
Lisa Madlberger, Ayu Purwarianti. (2016). "Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia ." Web.
1. Lisa Madlberger, Ayu Purwarianti. Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1290

A Regression Approach to Valence-Arousal Ratings of Words from Word

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17 November 2016 - 6:54am
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A Regression Approach to Valence-Arousal Ratings of Words from Word-PPT.pdf

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[1] , "A Regression Approach to Valence-Arousal Ratings of Words from Word", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1268. Accessed: Oct. 19, 2017.
@article{1268-16,
url = {http://sigport.org/1268},
author = { },
publisher = {IEEE SigPort},
title = {A Regression Approach to Valence-Arousal Ratings of Words from Word},
year = {2016} }
TY - EJOUR
T1 - A Regression Approach to Valence-Arousal Ratings of Words from Word
AU -
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1268
ER -
. (2016). A Regression Approach to Valence-Arousal Ratings of Words from Word. IEEE SigPort. http://sigport.org/1268
, 2016. A Regression Approach to Valence-Arousal Ratings of Words from Word. Available at: http://sigport.org/1268.
. (2016). "A Regression Approach to Valence-Arousal Ratings of Words from Word." Web.
1. . A Regression Approach to Valence-Arousal Ratings of Words from Word [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1268

On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation


Although uni-directional recurrent neural network language
model(RNNLM) has been very successful, it’s hard to train a
bi-directional RNNLM properly due to the generative nature of
language model. In this work, we propose to train bi-directional
RNNLM with noise contrastive estimation(NCE), since the
properities of NCE training will help the model to acheieve
sentence-level normalization. Experiments are conducted on
two hand-crafted tasks on the PTB data set: a rescore task and

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Authors:
Tianxing He, Yu Zhang, Jasha Droppo, Kai Yu
Submitted On:
16 October 2016 - 11:45am
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iscslp2016_poster_v2.pdf

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[1] Tianxing He, Yu Zhang, Jasha Droppo, Kai Yu, "On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1255. Accessed: Oct. 19, 2017.
@article{1255-16,
url = {http://sigport.org/1255},
author = {Tianxing He; Yu Zhang; Jasha Droppo; Kai Yu },
publisher = {IEEE SigPort},
title = {On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation},
year = {2016} }
TY - EJOUR
T1 - On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation
AU - Tianxing He; Yu Zhang; Jasha Droppo; Kai Yu
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1255
ER -
Tianxing He, Yu Zhang, Jasha Droppo, Kai Yu. (2016). On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation. IEEE SigPort. http://sigport.org/1255
Tianxing He, Yu Zhang, Jasha Droppo, Kai Yu, 2016. On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation. Available at: http://sigport.org/1255.
Tianxing He, Yu Zhang, Jasha Droppo, Kai Yu. (2016). "On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation." Web.
1. Tianxing He, Yu Zhang, Jasha Droppo, Kai Yu. On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1255

The Preliminary Study of Influence on Tone Perception from Segments

Paper Details

Authors:
Chong Cao, Yanlu Xie, Ju Lin, Qian Li, Jinsong Zhang
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15 October 2016 - 10:42pm
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the preliminary study of influence on tone perception from segments.pdf

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[1] Chong Cao, Yanlu Xie, Ju Lin, Qian Li, Jinsong Zhang, "The Preliminary Study of Influence on Tone Perception from Segments", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1253. Accessed: Oct. 19, 2017.
@article{1253-16,
url = {http://sigport.org/1253},
author = {Chong Cao; Yanlu Xie; Ju Lin; Qian Li; Jinsong Zhang },
publisher = {IEEE SigPort},
title = {The Preliminary Study of Influence on Tone Perception from Segments},
year = {2016} }
TY - EJOUR
T1 - The Preliminary Study of Influence on Tone Perception from Segments
AU - Chong Cao; Yanlu Xie; Ju Lin; Qian Li; Jinsong Zhang
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1253
ER -
Chong Cao, Yanlu Xie, Ju Lin, Qian Li, Jinsong Zhang. (2016). The Preliminary Study of Influence on Tone Perception from Segments. IEEE SigPort. http://sigport.org/1253
Chong Cao, Yanlu Xie, Ju Lin, Qian Li, Jinsong Zhang, 2016. The Preliminary Study of Influence on Tone Perception from Segments. Available at: http://sigport.org/1253.
Chong Cao, Yanlu Xie, Ju Lin, Qian Li, Jinsong Zhang. (2016). "The Preliminary Study of Influence on Tone Perception from Segments." Web.
1. Chong Cao, Yanlu Xie, Ju Lin, Qian Li, Jinsong Zhang. The Preliminary Study of Influence on Tone Perception from Segments [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1253

A Study on perceptual training of Japanese CSL Learner to Discriminate Mandarin Lexical Tones


In process of learning Chinese as a second language (CSL), Japanese natives have difficulties in tone perception. Among the four Chinese lexical tones, the tone pairs Tone 1-Tone 2 and Tone 1-Tone 4 are problematic for Japanese CSL beginners. In order to help them develop efficiently discriminating capability of the tone pairs, we designed a hybrid perceptual training scheme which combined adaptive training and high variability phonetic training.

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Authors:
Feiya Li, Yanlu Xie, Xiaomin Yu, Jinsong Zhang
Submitted On:
15 October 2016 - 12:55pm
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ISCSLP-paper177-oral.pdf

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[1] Feiya Li, Yanlu Xie, Xiaomin Yu, Jinsong Zhang, "A Study on perceptual training of Japanese CSL Learner to Discriminate Mandarin Lexical Tones", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1252. Accessed: Oct. 19, 2017.
@article{1252-16,
url = {http://sigport.org/1252},
author = { Feiya Li; Yanlu Xie; Xiaomin Yu; Jinsong Zhang },
publisher = {IEEE SigPort},
title = {A Study on perceptual training of Japanese CSL Learner to Discriminate Mandarin Lexical Tones},
year = {2016} }
TY - EJOUR
T1 - A Study on perceptual training of Japanese CSL Learner to Discriminate Mandarin Lexical Tones
AU - Feiya Li; Yanlu Xie; Xiaomin Yu; Jinsong Zhang
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1252
ER -
Feiya Li, Yanlu Xie, Xiaomin Yu, Jinsong Zhang. (2016). A Study on perceptual training of Japanese CSL Learner to Discriminate Mandarin Lexical Tones. IEEE SigPort. http://sigport.org/1252
Feiya Li, Yanlu Xie, Xiaomin Yu, Jinsong Zhang, 2016. A Study on perceptual training of Japanese CSL Learner to Discriminate Mandarin Lexical Tones. Available at: http://sigport.org/1252.
Feiya Li, Yanlu Xie, Xiaomin Yu, Jinsong Zhang. (2016). "A Study on perceptual training of Japanese CSL Learner to Discriminate Mandarin Lexical Tones." Web.
1. Feiya Li, Yanlu Xie, Xiaomin Yu, Jinsong Zhang. A Study on perceptual training of Japanese CSL Learner to Discriminate Mandarin Lexical Tones [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1252

Acoustic Correlates and Gender Effects in Production and Perception of Japanese Polite Speech


This study examines potential contribution of prosodic features and voice quality to the perception and production of Japanese polite speech as well as possible gender effects in politeness strategy.

Shi Shuju, Tsurutani Chiharu, Feng Xiaoli, Zhang Jinsong, Minematsu Nobuaki

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Authors:
Chiharu Tsurutani, Xiaoli Feng, Jinsong Zhang, Nobuaki Minematsu
Submitted On:
15 October 2016 - 11:31am
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Japanese politness

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[1] Chiharu Tsurutani, Xiaoli Feng, Jinsong Zhang, Nobuaki Minematsu, "Acoustic Correlates and Gender Effects in Production and Perception of Japanese Polite Speech", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1246. Accessed: Oct. 19, 2017.
@article{1246-16,
url = {http://sigport.org/1246},
author = {Chiharu Tsurutani; Xiaoli Feng; Jinsong Zhang; Nobuaki Minematsu },
publisher = {IEEE SigPort},
title = {Acoustic Correlates and Gender Effects in Production and Perception of Japanese Polite Speech},
year = {2016} }
TY - EJOUR
T1 - Acoustic Correlates and Gender Effects in Production and Perception of Japanese Polite Speech
AU - Chiharu Tsurutani; Xiaoli Feng; Jinsong Zhang; Nobuaki Minematsu
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1246
ER -
Chiharu Tsurutani, Xiaoli Feng, Jinsong Zhang, Nobuaki Minematsu. (2016). Acoustic Correlates and Gender Effects in Production and Perception of Japanese Polite Speech. IEEE SigPort. http://sigport.org/1246
Chiharu Tsurutani, Xiaoli Feng, Jinsong Zhang, Nobuaki Minematsu, 2016. Acoustic Correlates and Gender Effects in Production and Perception of Japanese Polite Speech. Available at: http://sigport.org/1246.
Chiharu Tsurutani, Xiaoli Feng, Jinsong Zhang, Nobuaki Minematsu. (2016). "Acoustic Correlates and Gender Effects in Production and Perception of Japanese Polite Speech." Web.
1. Chiharu Tsurutani, Xiaoli Feng, Jinsong Zhang, Nobuaki Minematsu. Acoustic Correlates and Gender Effects in Production and Perception of Japanese Polite Speech [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1246

Automatic Detection of Rhythmic Patterns in Native and L2 Speech: Chinese, Japanese, and Japanese L2 Chinese


This study explores possible contribution of speech rhythm to foreign accent. We conducted statistical analysis and realized automatic detection of rhythmic patterns on Mandarin Chinese, Japanese and Japanese second language learners (L2) of Chinese using interval-based and amplitude-based measures.

rhythm.pdf

PDF icon L2 speech rhythm (128 downloads)

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Authors:
Xiaoli Feng, Jingsong Zhang, Yanlu Xie
Submitted On:
15 October 2016 - 10:44am
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L2 speech rhythm

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[1] Xiaoli Feng, Jingsong Zhang, Yanlu Xie, "Automatic Detection of Rhythmic Patterns in Native and L2 Speech: Chinese, Japanese, and Japanese L2 Chinese", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1240. Accessed: Oct. 19, 2017.
@article{1240-16,
url = {http://sigport.org/1240},
author = {Xiaoli Feng; Jingsong Zhang; Yanlu Xie },
publisher = {IEEE SigPort},
title = {Automatic Detection of Rhythmic Patterns in Native and L2 Speech: Chinese, Japanese, and Japanese L2 Chinese},
year = {2016} }
TY - EJOUR
T1 - Automatic Detection of Rhythmic Patterns in Native and L2 Speech: Chinese, Japanese, and Japanese L2 Chinese
AU - Xiaoli Feng; Jingsong Zhang; Yanlu Xie
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1240
ER -
Xiaoli Feng, Jingsong Zhang, Yanlu Xie. (2016). Automatic Detection of Rhythmic Patterns in Native and L2 Speech: Chinese, Japanese, and Japanese L2 Chinese. IEEE SigPort. http://sigport.org/1240
Xiaoli Feng, Jingsong Zhang, Yanlu Xie, 2016. Automatic Detection of Rhythmic Patterns in Native and L2 Speech: Chinese, Japanese, and Japanese L2 Chinese. Available at: http://sigport.org/1240.
Xiaoli Feng, Jingsong Zhang, Yanlu Xie. (2016). "Automatic Detection of Rhythmic Patterns in Native and L2 Speech: Chinese, Japanese, and Japanese L2 Chinese." Web.
1. Xiaoli Feng, Jingsong Zhang, Yanlu Xie. Automatic Detection of Rhythmic Patterns in Native and L2 Speech: Chinese, Japanese, and Japanese L2 Chinese [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1240

Applying Connectionist Temporal Classification Objective Function to Chinese Mandarin Speech Recognition


This paper establishs CTC-based systems on Chinese Mandarin ASR task, three different level output units are explored: characters, context independent phonemes and context dependent phoneme. To make training stable we propose Newbob-Trn strategy, furthermore, blank label prior cost is proposed to improve the performance. Further, we establish the CTC-trained UniLSTM-RC model, which ensures the real-time requirement of an online system, meanwhile, brings performance gain on Chinese Mandarin ASR task.

Paper Details

Authors:
Pengrui Wang,Jie Li,Bo Xu
Submitted On:
17 October 2016 - 11:07am
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Applying Connectionist Temporal Classification Objective Function to Chinese Mandarin Speech Recognition.pptx

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[1] Pengrui Wang,Jie Li,Bo Xu, "Applying Connectionist Temporal Classification Objective Function to Chinese Mandarin Speech Recognition", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1231. Accessed: Oct. 19, 2017.
@article{1231-16,
url = {http://sigport.org/1231},
author = {Pengrui Wang;Jie Li;Bo Xu },
publisher = {IEEE SigPort},
title = {Applying Connectionist Temporal Classification Objective Function to Chinese Mandarin Speech Recognition},
year = {2016} }
TY - EJOUR
T1 - Applying Connectionist Temporal Classification Objective Function to Chinese Mandarin Speech Recognition
AU - Pengrui Wang;Jie Li;Bo Xu
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1231
ER -
Pengrui Wang,Jie Li,Bo Xu. (2016). Applying Connectionist Temporal Classification Objective Function to Chinese Mandarin Speech Recognition. IEEE SigPort. http://sigport.org/1231
Pengrui Wang,Jie Li,Bo Xu, 2016. Applying Connectionist Temporal Classification Objective Function to Chinese Mandarin Speech Recognition. Available at: http://sigport.org/1231.
Pengrui Wang,Jie Li,Bo Xu. (2016). "Applying Connectionist Temporal Classification Objective Function to Chinese Mandarin Speech Recognition." Web.
1. Pengrui Wang,Jie Li,Bo Xu. Applying Connectionist Temporal Classification Objective Function to Chinese Mandarin Speech Recognition [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1231

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