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» State Duration Modeling for HMM-Based Speech Synthesis
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TSP
2010
13 years 2 months ago
A multi-resolution hidden Markov model using class-specific features
We address the problem in signal classification applications, such as automatic speech recognition (ASR) systems that employ the hidden Markov model (HMM), that it is necessary to...
Paul M. Baggenstoss
CSL
1999
Springer
13 years 7 months ago
A hidden Markov-model-based trainable speech synthesizer
This paper presents a new approach to speech synthesis in which a set of cross-word decision-tree state-clustered context-dependent hidden Markov models are used to define a set o...
R. E. Donovan, Philip C. Woodland
ICASSP
2009
IEEE
14 years 2 months ago
Control of prosodic focus in corpus-based generation of fundamental frequency contours of Japanese based on the generation proce
A total corpus-based process of generating prosodic features from text is developed. The process first predicts pauses and phone durations, and then generates F0 contours. Since F...
Keiko Ochi, Keikichi Hirose, Nobuaki Minematsu
44
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ACII
2007
Springer
14 years 1 months ago
Facial Expression Synthesis Using PAD Emotional Parameters for a Chinese Expressive Avatar
Facial expression plays an important role in face to face communication in that it conveys nonverbal information and emotional intent beyond speech. In this paper, an approach for ...
Shen Zhang, Zhiyong Wu, Helen M. Meng, Lianhong Ca...
ICASSP
2010
IEEE
13 years 7 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