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ICASSP
2008
IEEE
14 years 2 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
NAACL
2010
13 years 5 months ago
Investigations into the Crandem Approach to Word Recognition
We suggest improvements to a previously proposed framework for integrating Conditional Random Fields and Hidden Markov Models, dubbed a Crandem system (2009). The previous authors...
Rohit Prabhavalkar, Preethi Jyothi, William Hartma...
CVPR
1998
IEEE
14 years 10 months ago
Action Recognition Using Probabilistic Parsing
A new approach to the recognition of temporal behaviors and activities is presented. The fundamental idea, inspired by work in speech recognition, is to divide the inference probl...
Aaron F. Bobick, Yuri A. Ivanov
BIOADIT
2004
Springer
13 years 11 months ago
Biologically Plausible Speech Recognition with LSTM Neural Nets
Abstract. Long Short-Term Memory (LSTM) recurrent neural networks (RNNs) are local in space and time and closely related to a biological model of memory in the prefrontal cortex. N...
Alex Graves, Douglas Eck, Nicole Beringer, Jü...
ICASSP
2011
IEEE
12 years 11 months ago
Multi-view and multi-objective semi-supervised learning for large vocabulary continuous speech recognition
Current hidden Markov acoustic modeling for large vocabulary continuous speech recognition (LVCSR) relies on the availability of abundant labeled transcriptions. Given that speech...
Xiaodong Cui, Jing Huang, Jen-Tzung Chien