Discriminative Training Using Noise Robust Integrated Features and Refined HMM Modeling

Discriminative Training Using Noise Robust Integrated Features and Refined HMM Modeling

The classical approach to build an automatic speech recognition (ASR) system uses different feature extraction methods at the front end and various parameter classification techniques at the back end. The Mel-frequency cepstral coefficients (MFCC) and perceptual linear prediction (PLP) techniques ar...

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Bibliographic Details
Main Authors: Dua Mohit, Aggarwal Rajesh Kumar, Biswas Mantosh
Format: Article
Language:English
Published: De Gruyter 2018-02-01
Series:Journal of Intelligent Systems
Subjects:
automatic speech recognition
mfcc
gfcc
genetic algorithm
pso
plp
discriminative training
mmi
mpe
Online Access:https://doi.org/10.1515/jisys-2017-0618

Internet

https://doi.org/10.1515/jisys-2017-0618

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