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Predicting prosodic words from lexical words - a first step towards predicting prosody from text

机译:从词汇词预测韵律词-从文本预测韵律的第一步

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Much remains unsolved in how to predict prosody from text for unlimited Mandarin Chinese TTS. The interactions and the rules between syntactic structure and prosodic structure are still unresolved challenges. By using part-of-speech (POS) tagging, for which text lexical information is required, we aim to find significant patterns of word grouping from analyzing real speech data and such lexical information. The paper reports discrepancies found between lexical words (LW) parsed from text and prosodic words (PW) annotated from speech data, and proposes a statistical model to predict PWs from LWs. In the statistical model, the length of the word and the tagging from POS are two essential features to predict PWs, and the results show approximately 90% of prediction for PWs; however, it does leave more room for extension. We believe that evidence from PW predictions is a first step towards building prosody models from text.
机译:在如何从无限制普通话TTS的文本中预测韵律方面,仍然有许多悬而未决的问题。句法结构和韵律结构之间的相互作用和规则仍未解决。通过使用词性(POS)标记,为此需要文本词法信息,我们旨在通过分析真实语音数据和此类词法信息来找到有效的词组模式。该论文报告了从文本解析的词汇词(LW)与从语音数据注释的韵律词(PW)之间发现的差异,并提出了一种统计模型来预测来自语音词的PW。在统计模型中,单词长度和来自POS的标记是预测PW的两个基本特征,结果显示约90%的PW预测。但是,它确实留出了更多的扩展空间。我们认为,来自PW预测的证据是从文本构建韵律模型的第一步。

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