Improved acoustic modeling for transcribing Arabic broadcast data

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