Arabic automatic segmentation system and its application for Arabic speech recognition system

Author

Nofal, Maged ; Abdel Kader, Nemat S. ; Abdel-Raheem, Esam ; El Henawy, M.

Author_Institution

Dept. of Electron. & Commun. Eng., Ain Shams Univ., Cairo

Volume

2

fYear

2003

fDate

30-30 Dec. 2003

Firstpage

697

Abstract

The paper presents an Arabic automatic segmentation system to be utilized in the development of an Arabic speech recognition system. The automatic segmentation system is used to label a speech database system that is used in the training of continuous, phoneme based speaker independent Hidden Markov Models. Our experiments showed that 7.8 % of the phoneme boundaries of automatic segmented data deviate from those that were manually segmented more than 30 milliseconds while 0.78 % deviate more than 70 milliseconds. Our experiments showed also that automatic segmentation led to improvement in speech recognition accuracy of 0.49 % for a 306 words bigram language model test and 0.14% for 1340 words bigram model

Keywords

audio databases; hidden Markov models; natural languages; speech recognition; Arabic automatic segmentation system; Arabic speech recognition system; bigram language model; hidden Markov models; phoneme based speaker; speech database system; Acoustic signal detection; Automatic testing; Cepstral analysis; Database systems; Hidden Markov models; Labeling; Loudspeakers; Natural languages; Speech recognition; Viterbi algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2003 IEEE 46th Midwest Symposium on

Conference_Location

Cairo

ISSN

1548-3746

Print_ISBN

0-7803-8294-3

Type

conf

DOI

10.1109/MWSCAS.2003.1562382

Filename

1562382