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Exploitation of Morphological Structures in Large Vocabulary Arabic Speech Recognition

机译:大词汇量阿拉伯语语音识别中形态结构的开发

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This paper presents a new approach for large vocabulary Arabic speech recognition based on exploiting the morphological structures of the Arabic language. In this model, word discrimination is achieved by a hybrid analysis scheme, where vowels are described in detail while consonants are classified according to broad phonetic classes. Different phonetic classification strategies are used to describe two large vocabulary lexicons. The results show that about 83% of the 10,000 test Arabic words can be uniquely represented by using 7 broad phonetic classes for consonants and six classes for vowels. In this case, the maximum number of words having the same phonetic labelling is 6. This paper summarises the results of ten different phonetic classification schemes and discusses their implication for a large vocabulary speech recognition system.
机译:本文提出了一种基于阿拉伯语形态结构的大词汇量阿拉伯语语音识别新方法。在此模型中,通过混合分析方案实现了单词辨别,其中详细描述了元音,同时根据广泛的语音类别对辅音进行了分类。不同的语音分类策略用于描述两个大词汇词典。结果表明,在10,000个测试阿拉伯语单词中,约有83%可以通过使用7个宽泛的语音辅音类和6个元音语音类来唯一表示。在这种情况下,具有相同语音标记的单词的最大数量为6。本文总结了十种不同的语音分类方案的结果,并讨论了它们对大型词汇语音识别系统的影响。

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