Robust speech recognition with selective input data to a NN classifier

被引：0

作者：

Cong, L ^{[1
]}

Asghar, S ^{[1
]}

机构：

[1] Adv Micro Devices, Austin, TX 78741 USA

来源：

INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED PROCESSING TECHNIQUES AND APPLICATIONS, VOLS I-IV, PROCEEDINGS | 1998年

关键词：

neural networks; speech recognition;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents the new robust IWSR systems which provide selective input data to a neural network in response to speech signal to acoustic noise ratios to improve speech recognition system performance The proposed robust isolated word speech recognition systems employ FMQ/MQ as the spectral labelling process, followed by a Hidden Markov Model (HMM), or a HMM and Neural Network (HMM/MLP) classification techniqut. NOSEX92 has been used as the speech and noise database. This robust performance ensures that a recognition accuracy of the order 98.9% and 95% is obtained with SNR at 10 dB and 0 dB respectively.

引用

页码：1817 / 1824

页数：8

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