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» Signal Processing for Robust Speech Recognition
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ICASSP
2011
IEEE
14 years 8 months ago
Named entity recognition from Conversational Telephone Speech leveraging Word Confusion Networks for training and recognition
Named Entity (NE) recognition from the results of Automatic Speech Recognition (ASR) is challenging because of ASR errors. To detect NEs, one of the options is to use a statistica...
Gakuto Kurata, Nobuyasu Itoh, Masafumi Nishimura, ...
ICASSP
2009
IEEE
15 years 11 months ago
A criterion for the enhancement of time-frequency masks in missing data recognition
Despite their effectiveness for robust speech processing, missing data techniques are vulnerable to errors in the classification of the input speech signal’s time-frequency poi...
Daniel Pullella, Roberto Togneri
CIIT
2004
15 years 5 months ago
Signal processing tools for speech recognition
This paper describes the design and development of a set of signal processing software tools for speech recognition. The tools were developed for inclusion in a comprehensive publ...
Hualin Gao, Richard Duncan, Julie Baca, Joseph Pic...
ICASSP
2011
IEEE
14 years 8 months ago
Comparing multilayer perceptron to Deep Belief Network Tandem features for robust ASR
In this paper, we extend the work done on integrating multilayer perceptron (MLP) networks with HMM systems via the Tandem approach. In particular, we explore whether the use of D...
Oriol Vinyals, Suman V. Ravuri
ICASSP
2008
IEEE
15 years 11 months ago
Multisensor multiband cross-energy tracking for feature extraction and recognition
In this paper, we present a multisensor multiband energy tracking scheme for robust feature extraction in noisy environments. We introduce a multisensor feature extraction algorit...
Stamatios Lefkimmiatis, Petros Maragos, Athanassio...