Improvement on Automatic Speech Recognition Using Micro-genetic Algorithm

2012 ◽  
Author(s):  
Santiago Omar Caballero Morales ◽  
Yara Perez Maldonado ◽  
Felipe Trujillo Romero
Keyword(s):  
Genetic Algorithm ◽  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Micro Genetic Algorithm

A Hybrid System for Automatic Infant Cry Recognition II

2011 ◽  
pp. 867-872
Author(s):  
Carlos Alberto Reyes-García ◽  
Sandra E. Barajas ◽  
Esteban Tlelo-Cuautle ◽  
Orion Fausto Reyes-Galaviz
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Speech Recognition ◽  
Membership Function ◽  
Automatic Speech Recognition ◽  
Hybrid System ◽  
Learning Rate ◽  
Data Sets ◽  
Infant Cry ◽  
Pattern Processing

Automatic Infant Cry Recognition (AICR) process is basically a problem of pattern processing, very similar to the Automatic Speech Recognition (ASR) process (Huang, Acero, Hon, 2001). In AICR first we perform acoustical analysis, where the crying signal is analyzed to extract the more important acoustical features, like; LPC, MFCC, etc. (Cano, Escobedo and Coello, 1999). The obtained characteristics are represented by feature vectors, and each vector represents a pattern. These patterns are then classified in their corresponding pathology (Ekkel, 2002). In the reported case we are automatically classifying cries from normal, deaf and asphyxiating infants. We use a genetic algorithm to find several optimal parameters needed by the Fuzzy Relational Neural Network FRNN (Reyes, 1994), like; the number of linguistic properties, the type of membership function, the method to calculate the output and the learning rate. The whole model has been tested on several data sets for infant cry classification. The process, as well as some results, is described.

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

Contextual Recovery of Out-of-Lattice Named Entities in Automatic Speech Recognition

2019 ◽  
Author(s):  
Jack Serrino ◽  
Leonid Velikovich ◽  
Petar Aleksic ◽  
Cyril Allauzen
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Named Entities
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