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Multi-Reference Evaluation for Dialectal Speech Recognition System: A Study for Egyptian ASR

机译:方言语音识别系统的多参考评估:埃及ASR研究

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Dialectal Arabic has no standard orthographic representation. This creates a challenge when evaluating an Automatic Speech Recognition (ASR) system for dialect. Since the reference transcription text can vary widely from one user to another, we propose an innovative approach for evaluating dialectal speech recognition using Multi-References. For each recognized speech segments, we ask five different users to transcribe the speech. We combine the alignment for the multiple references, and use the combined alignment to report a modified version of Word Error Rate (WER). This approach is in favor of accepting a recognized word if any of the references typed it in the same form. Our method proved to be more effective in capturing many correctly recognized words that have multiple acceptable spellings. The initial WER according to each of the five references individually ranged between 76.4% to 80.9%. When considering all references combined, the Multi-References MR-WER was found to be 53%.
机译:方言阿拉伯语没有标准的正字法表示形式。在评估针对方言的自动语音识别(ASR)系统时,这带来了挑战。由于参考转录文本在一个用户与另一个用户之间的差异很大,因此我们提出了一种创新的方法,用于使用“多参考”来评估方言语音识别。对于每个识别的语音片段,我们要求五个不同的用户转录语音。我们将多个参考的对齐方式组合在一起,并使用组合的对齐方式报告字错误率(WER)的修改版本。如果任何参考文献以相同的形式键入了公认的单词,则此方法有利于接受该单词。我们的方法被证明在捕获具有多个可接受的拼写的许多正确识别的单词时更有效。根据这五个参考文献中的每一个的初始WER分别在76.4%至80.9%之间。当考虑所有参考组合时,发现多参考MR-WER为53%。

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