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» Signal Processing for Robust Speech Recognition
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LREC
2010
173views Education» more  LREC 2010»
15 years 6 months ago
Transcriber Driving Strategies for Transcription Aid System
Speech recognition technology suffers from a lack of robustness which limits its usability for fully automated speech-to-text transcription, and manual correction is generally req...
Grégory Senay, Georges Linares, Benjamin Le...
ICANN
2007
Springer
15 years 10 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...
ICASSP
2011
IEEE
14 years 8 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
ICASSP
2011
IEEE
14 years 8 months ago
Investigation of acoustic units for LVCSR systems
One important issue in designing state-of-the-art LVCSR systems is the choice of acoustic units. Context dependent (CD) phones remain the dominant form of acoustic units. They can...
Xunying Liu, Mark John Francis Gales, Jim L. Hiero...
ICASSP
2011
IEEE
14 years 8 months ago
An unconstrained method for lip detection in color images
The use of visual information derived from accurate lip extraction, can provide features invariant to noise perturbation for speech recognition systems and can be also used in a w...
Evangelos Skodras, Nikolaos D. Fakotakis