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Subword Speech Recognition for Detection of Unseen Words

机译:次字语音识别,用于检测看不见的单词

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We present a novel approach to building a subword speech recognizer for the task of phonetic keyword search. The recognizer, which uses short fixed-length phonetic units, is trained with phonetic transcripts that are segmented into all possible substrings of 1, 2 and 3 phones, using a lattice representation to accommodate the overlapping units. We compare the keyword search accuracy of. the proposed system with systems that use words, graphenes, variable-length phonetic units and context-dependent phones. Experiments with Spanish CTS data show that the proposed subword recognizer outperforms other subword systems in terms of phonetic keyword search accuracy measured oh queries that consist of words not present in the training data.
机译:我们提出了一种新的方法来构建子字语音识别器的语音关键字搜索任务。使用短固定长度拼音单元的识别器训练,其使用晶格表示来划分为1,2和3个电话的所有可能的子网格,以容纳重叠单元。我们比较关键字搜索准确性。具有使用单词,图形,可变长度语音单元和上下文相关电话的系统的系统。使用西班牙语CTS数据的实验表明,所提出的子字识别器在语音关键词搜索精度方面优于其他子字系统,测量OH查询,该oh查询由训练数据中不存在的单词组成。

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