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
收藏
页码：1817 / 1824
页数：8
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