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» A flat direct model for speech recognition
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ICPR
2006
IEEE
14 years 9 months ago
Detecting Coarticulation in Sign Language using Conditional Random Fields
Coarticulation is one of the important factors that makes automatic sign language recognition a hard problem. Unlike in speech recognition, coarticulation effects in sign language...
Ruiduo Yang, Sudeep Sarkar
INTERSPEECH
2010
13 years 2 months ago
Language model cross adaptation for LVCSR system combination
State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often combine outputs from multiple subsystems developed at different sites. Cross system adaptatio...
Xunying Liu, Mark J. F. Gales, Philip C. Woodland
ICASSP
2011
IEEE
12 years 11 months ago
Training of error-corrective model for ASR without using audio data
This paper introduces a method to train an error-corrective model for Automatic Speech Recognition (ASR) without using audio data. In existing techniques, it is assumed that sufï¬...
Gakuto Kurata, Nobuyasu Itoh, Masafumi Nishimura
ICANN
2007
Springer
14 years 2 months ago
Multi-dimensional Recurrent Neural Networks
Abstract. Recurrent neural networks (RNNs) have proved effective at one dimensional sequence learning tasks, such as speech and online handwriting recognition. Some of the properti...
Alex Graves, Santiago Fernández, Jürge...
PAMI
2008
160views more  PAMI 2008»
13 years 7 months ago
Emotion Recognition Based on Physiological Changes in Music Listening
Little attention has been paid so far to physiological signals for emotion recognition compared to audiovisual emotion channels such as facial expression or speech. This paper inve...
Jonghwa Kim, Elisabeth André