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
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 ...
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...
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,...
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...