Syllable Based Continuous Speech Recognizer With Varied Length Maximum Likelihood Character Segmentation

被引：0

作者：

Ganesh, Akila A. ^{[1
]}

Ravichandran, Chandra ^{[2
]}

机构：

[1] DJ Acad Managerial Excellence, Dept Comp Sci, Coimbatore, Tamil Nadu, India

[2] Dr SNS Rajalakshmi Coll Arts & Sci, Dept Comp Sci, Coimbatore, Tamil Nadu, India

来源：

2013 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI) | 2013年

关键词：

Syllable; Segmentation; Maximum Likelihood (ML) segmentation; Varied Length Maximum Likelihood Segmentation (VLML);

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Speech is the most natural and quick mode of transforming and sharing information. To automate the process of speech production and perception, many researches are carried out for more than five decades. For an Automatic speech Recognition (ASR) of a large or unlimited vocabulary, a recognition unit smaller than word size is necessary. In this paper a new approach for segmenting the input utterance into individual characters is presented. The accuracy of boundary detection of baseline Maximum Likelihood (ML) Algorithm and the proposed algorithm is also compared and discussed.

引用

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页码：935 / 940

页数：6

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