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CSL
2016
Springer
8 years 19 days ago
Integrating articulatory data in deep neural network-based acoustic modeling
Hybrid deep neural network–hidden Markov model (DNN-HMM) systems have become the state-of-the-art in automatic speech recognition. In this paper we experiment with DNN-HMM phone...
Leonardo Badino, Claudia Canevari, Luciano Fadiga,...
CSL
2016
Springer
8 years 19 days ago
Capitalizing on musical rhythm for prosodic training in computer-aided language learning
Language transfer creates a challenge for Chinese (L1) speakers in acquiring English (L2) rhythm. This appears to be a widely encountered difficulty among foreign learners of Eng...
Hao Wang, Peggy Mok, Helen Meng
CSL
2016
Springer
8 years 19 days ago
ALISA: An automatic lightly supervised speech segmentation and alignment tool
This paper describes the ALISA tool, which implements a lightly supervised method for sentence-level alignment of speech with imperfect transcripts. Its intended use is to enable ...
Adriana Stan, Yoshitaka Mamiya, Junichi Yamagishi,...
CSL
2016
Springer
8 years 19 days ago
Application of continuous state Hidden Markov Models to a classical problem in speech recognition
This paper describes an optimal algorithm using continuous state Hidden Markov Models for solving the HMS decoding problem, which is the problem of recovering an underlying sequen...
Colin J. Champion, S. M. Houghton
CSL
2016
Springer
8 years 19 days ago
Articulatory feature based continuous speech recognition using probabilistic lexical modeling
Phonological studies suggest that the typical subword units such as phones or phonemes used in automatic speech recognition systems can be decomposed into a set of features based ...
Ramya Rasipuram, Mathew Magimai-Doss
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