BROAD PHONETIC CLASSIFICATION AND SEGMENTATION OF CONTINUOUS SPEECH BY MEANS OF NEURAL NETWORKS AND DYNAMIC-PROGRAMMING

被引：6

作者：

MARTENS, JP

DEPUYDT, L

机构：

[1] University of Ghent, Laboratory for Electronics and Metrology, B-9000 Gent

来源：

SPEECH COMMUNICATION | 1991年 / 10卷 / 01期

关键词：

NEURAL NETWORKS; BROAD PHONETIC CLASSIFICATION; SEGMENTATION;

D O I：

10.1016/0167-6393(91)90029-S

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

We describe the broad phonetic classification and segmentation of continuous speech. We have trained a multilayered neural network to produce broad phonetic class hypotheses which were used as inputs to a multi-level segmentation algorithm based on dynamic programming. Evaluation of our algorithm on a multi-speaker database of continuously spoken number strings has demonstrated excellent segmentation and classification performances. © 1991.

引用

页码：81 / 90

页数：10

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