Alignment of transcription to the speech finds applications in video subtitling, human–computer interaction by means of natural language communication, etc. In spite of many advancements, alignment of transcription to speech remains a challenging task and may become even more challenging for dysarthric speech. Dysarthria is a motor speech disorder resulting from damaged peripheral or central nervous system and causes slow speaking rate, pronunciation deviations, and prolonged pause interval between words and syllables. One of the problems in aligning dysarthric speech to text is the presence of repetition. Repetition can be at syllable/word/phrase level. In this work, we proposed an algorithm for syllable boundary detection followed by syllable repetition detection in dysarthric speech. When a syllable is found to be repeated, that syllable is repeated automatically in the transcription also. Modified transcription is given to the aligner along with the dysarthric speech. The proposed system when tested for word alignment with 15 utterances containing 146 words resulted in root mean square error (RMSE) of 0.138 when compared with the existing work in the literature, which gives an RMSE of 0.276.

中文翻译：

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基于重复检测的构音障碍语音改进语音与文本对齐

转录与语音的对齐在视频字幕、通过自然语言通信的人机交互等方面得到了应用。尽管取得了许多进步，但转录与语音的对齐仍然是一项具有挑战性的任务，对于构音障碍语音可能变得更具挑战性。构音障碍是一种由外周或中枢神经系统受损引起的运动性言语障碍，会导致语速缓慢、发音偏差以及单词和音节之间的停顿间隔延长。将构音障碍语音与文本对齐的问题之一是重复的存在。重复可以在音节/单词/短语级别。在这项工作中，我们提出了一种用于音节边界检测的算法，然后是构音障碍语音中的音节重复检测。当发现一个音节重复时，该音节也在转录中自动重复。修改后的转录与构音障碍语音一起提供给矫正器。与文献中的现有工作相比，所提出的系统在用包含 146 个单词的 15 个话语进行单词对齐测试时，均方根误差 (RMSE) 为 0.138，RMSE 为 0.276。