Improved acoustic modeling for transcribing Arabic broadcast data
Lori F Lamel, Abdel Messaoudi, Jean‐Luc Gauvain · 2007
ABSTRACT This paper summarizes our recent progress in improving theautomatic transcription of Arabic broadcast audio data, andsome efforts to address the challenges of the broadcast con-versational speech. Our efforts are aimed at improving theacoustic, pronunciation and language models taking into ac-count specificities of the Arabic language. In previous work wedemonstrated that explicit modeling of short vowels improvedrecognition performance, even when producing non-vocalizedhypotheses. In addition to modeling short vowels, consonantgemination and nunation are now explicitly modeled, alterna-tive pronunciations have been introduced to better represent di-alectical variants, and a duration model has been integrated.In order to facilitate training on Arabic audio data with non-vocalized transcripts a generic vowel model has been intro-duced. Compared with the previous system (used in the 2006GALE evaluation) the relative word error rate has been reducedby over 10%. Index Terms – Speech recognition, Arabic, broadcast news,broadcast conversations