Improving Automatic Speech Recognition Containing Additive Noise Using Deep Denoising Autoencoders of LSTM Networks

2016 ◽  
pp. 354-361 ◽  
Author(s):  
Marvin Coto-Jiménez ◽  
John Goddard-Close ◽  
Fabiola Martínez-Licona
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Additive Noise ◽  
Deep Denoising Autoencoders

scholarly journals Comparative Evaluation of Single-Channel MMSE-Based Noise Reduction Schemes for Speech Recognition

2010 ◽  
Vol 2010 ◽  
pp. 1-6 ◽  
Author(s):  
Emanuele Principi ◽  
Simone Cifani ◽  
Rudy Rotili ◽  
Stefano Squartini ◽  
Francesco Piazza
Keyword(s):  
Feature Extraction ◽  
Speech Recognition ◽  
Noise Reduction ◽  
Automatic Speech Recognition ◽  
Comparative Evaluation ◽  
Scientific Community ◽  
Additive Noise ◽  
Single Channel ◽  
Acoustic Conditions

One of the big challenges in the field of Automatic Speech Recognition (ASR) consists in developing suitable solutions able to work properly also in adverse acoustic conditions, like in presence of additive noise and/or in reverberant rooms. Recently a certain attention has been paid to deeply integrate the noise suppressor in the feature extraction pipeline. In this paper, different single-channel MMSE-based noise reduction schemes have been implemented both in the frequency and cepstral domains and the related recognition performances evaluated on the AURORA2 and AURORA4 databases, therefore providing a useful reference for the scientific community.

Using Clinician Annotations to Improve Automatic Speech Recognition of Stuttered Speech

2016 ◽  
Author(s):  
Peter A. Heeman ◽  
Rebecca Lunsford ◽  
Andy McMillin ◽  
J. Scott Yaruss
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition

Multi-Scale Context Adaptation for Improving Child Automatic Speech Recognition in Child-Adult Spoken Interactions

2017 ◽  
Author(s):  
Manoj Kumar ◽  
Daniel Bone ◽  
Kelly McWilliams ◽  
Shanna Williams ◽  
Thomas D. Lyon ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Context Adaptation ◽  
Multi Scale

Phoneme-to-Grapheme Conversion Based Large-Scale Pre-Training for End-to-End Automatic Speech Recognition

2020 ◽  
Author(s):  
Ryo Masumura ◽  
Naoki Makishima ◽  
Mana Ihori ◽  
Akihiko Takashima ◽  
Tomohiro Tanaka ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Large Scale ◽  
End To End
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