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» Adapting acoustic and lexical models to dysarthric speech
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ICASSP
2011
IEEE
12 years 9 months ago
Acoustic model training for non-audible murmur recognition using transformed normal speech data
In this paper we present a novel approach to acoustic model training for non-audible murmur (NAM) recognition using normal speech data transformed into NAM data. NAM is extremely ...
Denis Babani, Tomoki Toda, Hiroshi Saruwatari, Kiy...
ICASSP
2010
IEEE
13 years 5 months ago
Vocabulary and language model adaptation using just one speech file
This paper investigates unsupervised vocabulary and language model self-adaptation (VLA) from just one speech file using the web as a knowledge source and without prior knowledge...
Sha Meng, Kishan Thambiratnam, Yimeng Lin, Lifang ...
SPEECH
2010
89views more  SPEECH 2010»
13 years 11 days ago
Which words are hard to recognize? Prosodic, lexical, and disfluency factors that increase speech recognition error rates
Despite years of speech recognition research, little is known about which words tend to be misrecognized and why. Previous work has shown that errors increase for infrequent words...
Sharon Goldwater, Daniel Jurafsky, Christopher D. ...
LREC
2008
110views Education» more  LREC 2008»
13 years 7 months ago
Creation of Learner Corpus and Its Application to Speech Recognition
Some big languages like English are spoken by a lot of people whose mother tongues are different from. Their second languages often have not only distinct accent but also differen...
Hiroki Yamazaki, Keisuke Kitamura, Takashi Harada,...
CORR
2004
Springer
128views Education» more  CORR 2004»
13 years 5 months ago
Unsupervised Topic Adaptation for Lecture Speech Retrieval
We are developing a cross-media information retrieval system, in which users can view specific segments of lecture videos by submitting text queries. To produce a text index, the ...
Atsushi Fujii, Katunobu Itou, Tomoyosi Akiba, Tets...