Multi-input Multi-output Beta Wavelet Network: Modeling of Acoustic Units for Speech Recognition

11/08/2012
by   Ridha Ejbali, et al.
0

In this paper, we propose a novel architecture of wavelet network called Multi-input Multi-output Wavelet Network MIMOWN as a generalization of the old architecture of wavelet network. This newel prototype was applied to speech recognition application especially to model acoustic unit of speech. The originality of our work is the proposal of MIMOWN to model acoustic unit of speech. This approach was proposed to overcome limitation of old wavelet network model. The use of the multi-input multi-output architecture will allows training wavelet network on various examples of acoustic units.

READ FULL TEXT
research
01/11/2016

Environmental Noise Embeddings for Robust Speech Recognition

We propose a novel deep neural network architecture for speech recogniti...
research
05/06/2022

A Highly Adaptive Acoustic Model for Accurate Multi-Dialect Speech Recognition

Despite the success of deep learning in speech recognition, multi-dialec...
research
10/29/2020

Robust Raw Waveform Speech Recognition Using Relevance Weighted Representations

Speech recognition in noisy and channel distorted scenarios is often cha...
research
12/19/2017

Subword and Crossword Units for CTC Acoustic Models

This paper proposes a novel approach to create an unit set for CTC based...
research
10/31/2021

Revisiting joint decoding based multi-talker speech recognition with DNN acoustic model

In typical multi-talker speech recognition systems, a neural network-bas...
research
06/27/2017

Acoustic Modeling Using a Shallow CNN-HTSVM Architecture

High-accuracy speech recognition is especially challenging when large da...
research
01/30/2020

Oral Billiards

We propose a physical model of speech to explain its precision and robus...

Please sign up or login with your details

Forgot password? Click here to reset