Advances in Arabic broadcast news transcription at RWTH

David Rybach, Stefan Hahn, C. Gollan, R. Schlüter, H. Ney
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引用次数: 30

Abstract

This paper describes the RWTH speech recognition system for Arabic. Several design aspects of the system, including cross-adaptation, multiple system design and combination, are analyzed. We summarize the semi-automatic lexicon generation for Arabic using a statistical approach to grapheme-to-phoneme conversion and pronunciation statistics. Furthermore, a novel ASR-based audio segmentation algorithm is presented. Finally, we discuss practical approaches for parallelized acoustic training and memory efficient lattice rescoring. Systematic results are reported on recent GALE evaluation corpora.
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工业大学阿拉伯语广播新闻转录的进展
本文介绍了RWTH阿拉伯语语音识别系统。分析了系统的交叉适应、多系统设计和组合等几个设计方面的问题。我们总结了阿拉伯语半自动词汇生成使用的统计方法,字形音素转换和发音统计。在此基础上,提出了一种新的基于asr的音频分割算法。最后,我们讨论了并行声学训练和高效记忆点阵重记的实际方法。系统地报道了最近的GALE评价语料库的结果。
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Predictive linear transforms for noise robust speech recognition Development of a phonetic system for large vocabulary Arabic speech recognition Error simulation for training statistical dialogue systems An enhanced minimum classification error learning framework for balancing insertion, deletion and substitution errors Monolingual and crosslingual comparison of tandem features derived from articulatory and phone MLPS
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