Categorization of Unorganized Text Corpora for better Domain-Specific Language Modeling

Advances in Electrical and Electronic Engineering

Jozef Juhar¹  Jan Stas¹  Daniel Zlacky¹  Daniel Hladek¹ 

[1] Department of Electronics and Multimedia CommunicationsFaculty of Electrical Engineering and InformaticsTechnical University of KosiceKosice;

关键词: language modeling;    large vocabulary continuous speech recognition;    similarity measure;    term weighting;    text categorization;    topic detection.;   

DOI  :  10.15598/aeee.v11i5.897

来源: DOAJ

【 摘 要 】

This paper describes the process of categorization of unorganized text data gathered from the Internet to the in-domain and out-of-domain data for better domain-specific language modeling and speech recognition. An algorithm for text categorization and topic detection based on the most frequent key phrases is presented. In this scheme, each document entered into the process of text categorization is represented by a vector space model with term weighting based on computing the term frequency and inverse document frequency. Text documents are then classified to the in-domain and out-of-domain data automatically with predefined threshold using one of the selected distance/similarity measures comparing to the list of key phrases. The experimental results of the language modeling and adaptation to the judicial domain show significant improvement in the model perplexity about 19 % and decreasing of the word error rate of the Slovak transcription and dictation system about 5,54 %, relatively.

【 授权许可】

Unknown