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A new syllable-lattice based approach for Mandarin spoken document retrieval

机译:一种基于音节格的汉语普通话语音文档检索方法

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In our Mandarin spoken document retrieval system, the effects of both retrieval source and retrieval model are considered. For the retrieval source, the syllable-lattice is adopted which can ameliorate the effect of speech recognition error on document retrieval. For the retrieval model, the document length prior is combined with Jelinek-Mercer smoothing technique, which is widely applied in text document retrieval model. As far as we know, the combination of syllable lattice and retrieval model based on the document length prior is firstly introduced for spoken document retrieval. Experimental results show that the retrieval performance of lattice-based method outperforms that of 1-best method. Further more, in the retrieval model with the document length priors, lattice-based approach can achieve the best performance, which can improve about 30%.
机译:在我们的普通话语音文档检索系统中,考虑了检索源和检索模型的效果。对于检索源,采用音节格可以减轻语音识别错误对文档检索的影响。对于检索模型,将文档长度先验与Jelinek-Mercer平滑技术相结合,该技术已广泛应用于文本文档检索模型中。据我们所知,首先引入了基于文档长度的音节格和检索模型的结合,用于语音文档的检索。实验结果表明,基于格的方法的检索性能优于1-最佳方法。此外,在具有先验文档长度的检索模型中,基于格的方法可实现最佳性能,可提高约30%。

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