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ICASSP
2008
IEEE
13 years 10 months ago
Rhetorical-State Hidden Markov Models for extractive speech summarization
We propose an extractive summarization system with a novel non-generative probabilistic framework for speech summarization. One of the most underutilized features in extractive su...
Pascale Fung, Ricky Ho Yin Chan, Justin Jian Zhang
ICASSP
2010
IEEE
13 years 4 months ago
Learning deep rhetorical structure for extractive speech summarization
Extractive summarization of conference and lecture speech is useful for online learning and references. We show for the first time that deep(er) rhetorical parsing of conference ...
Justin Jian Zhang, Pascale Fung
TSP
2010
12 years 11 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
PAA
2006
13 years 4 months ago
Audio-visual sports highlights extraction using Coupled Hidden Markov Models
We present our studies on the application of Coupled Hidden Markov Models(CHMMs) to sports highlights extraction from broadcast video using both audio and video information. First,...
Ziyou Xiong
ICASSP
2011
IEEE
12 years 8 months ago
HNM-based MFCC+F0 extractor applied to statistical speech synthesis
Currently, the statistical framework based on Hidden Markov Models (HMMs) plays a relevant role in speech synthesis, while voice conversion systems based on Gaussian Mixture Model...
Daniel Erro, Iñaki Sainz, Eva Navas, Inma H...