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» A speech recognition and synthesis tool
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ICMCS
2009
IEEE
189views Multimedia» more  ICMCS 2009»
14 years 7 months ago
Emotion recognition from speech VIA boosted Gaussian mixture models
Gaussian mixture models (GMMs) and the minimum error rate classifier (i.e. Bayesian optimal classifier) are popular and effective tools for speech emotion recognition. Typically, ...
Hao Tang, Stephen M. Chu, Mark Hasegawa-Johnson, T...
CHI
2006
ACM
15 years 10 months ago
The effect of speech recognition accuracy rates on the usefulness and usability of webcast archives
The widespread availability of broadband connections has led to an increase in the use of Internet broadcasting (webcasting). Most webcasts are archived and accessed numerous time...
Cosmin Munteanu, Ronald Baecker, Gerald Penn, Elai...
74
Voted
TSD
2010
Springer
14 years 8 months ago
Diagnostics for Debugging Speech Recognition Systems
Modern speech recognition applications are becoming very complex program packages. To understand the error behaviour of the ASR systems, a special diagnosis - a procedure or a tool...
Milos Cernak
ACL
2012
13 years 13 hour ago
Fast Syntactic Analysis for Statistical Language Modeling via Substructure Sharing and Uptraining
Long-span features, such as syntax, can improve language models for tasks such as speech recognition and machine translation. However, these language models can be difficult to u...
Ariya Rastrow, Mark Dredze, Sanjeev Khudanpur
80
Voted
ICASSP
2010
IEEE
14 years 9 months ago
HMM-based sequence-to-frame mapping for voice conversion
Voice conversion can be reduced to a problem to find a transformation function between the corresponding speech sequences of two speakers. Perhaps the most voice conversions meth...
Yu Qiao, Daisuke Saito, Nobuaki Minematsu