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Speech Feature Denoising and Dereverberation via Deep Autoencoders for Noisy Reverberant Speech Recognition
robust speech recognition feature denoising denoising autoencoder deep neural network
2014/11/27
Denoising autoencoders (DAs) have shown success in generating robust features for images, but there has been limited work in applying DAs for speech. In this paper we present a deep denoising autoenco...
Multi-level Context-dependent Acoustic Modeling for Automatic Speech Recognition
Multi-level Context-dependent Acoustic Modeling Automatic Speech Recognition
2014/11/27
In this paper, we propose a multi-level, contextdependent acoustic modeling framework for automatic speech recognition. For each context-dependent unit considered by the recognizer, we construct a set...
An Efferent-Inspired Auditory Model Front-End for Speech Recognition
efferent auditory model feature extraction
2014/11/27
In this paper, we investigate a closed-loop auditory model and explore its potential as a feature representation for speech recognition. The closed-loop representation consists of an auditory-based, e...
A Back-off Discriminative Acoustic Model for Automatic Speech Recognition
context-dependent acoustic modeling back-off acoustic models discriminative training
2014/11/27
In this paper we propose a back-off discriminative acoustic model for Automatic Speech Recognition (ASR). We use a set of broad phonetic classes to divide the classification problem originating from c...
Research Developments and Directions in Speech Recognition and Understanding, Part 1
Research Developments Speech Recognition Understanding
2014/11/27
To advance research, it isimportant to identify prom-ising future research direc-tions, especially those thathave not been adequately pursued or funded in the past. The working group producing this ar...
THE PHASE SPECTRA BASED FEATURE FOR ROBUST SPEECH RECOGNITION
Group delay function Phase Spectrum Robust phoneme recognition
2010/1/11
Speech recognition in adverse environment is one of the major issue in
automatic speech recognition nowadays. While most current speech recognition system
show to be highly efficient for ideal envir...
Audio-Visual Speech Recognition using Red Exclusion and Neural Networks
Audio-Visual Speech Recognition Feature Extraction Neural Networks Sensor Fusion
2014/3/12
Automatic speech recognition (ASR) performs well under restricted conditions, but performance degrades in noisy environments. Audio-Visual Speech Recognition(AVSR) combats this by incorporating a visu...