基于发音特征的汉语发音偏误自动标注

针对发音偏误检测系统语音标注费时、费力和标注不一致的问题, 基于发音特征, 构建偏误检测系统, 给出Top-N的识别结果, 通过praat软件呈现机器初步标注文本, 在此基础上进行人工二次标注。实验结果表明, 与单纯的人工标注相比, 所提出的自动标注加人工二次标注方法在标注一致性上从80.7%提高到92.48%, 平均每个句子的标注时间从10分钟减少到3分钟。所提方法有效地提高了人工标注的效率, 可以在有限时间内为识别系统提供更多可靠的标注语料。

A Study of Articulatory Features Based Detection of Mandrain Pronunciation Erroneous Tendency for Automatic Annotation

For the purpose of relieving the time cost and inconformity in annotation, the authors use an articulatory features based mispronunciation detection system to give an Top-N feedback and use this feedback to assist manual annotation. As a result, the consistency rate of phoneme labels in proposed system increases from 80.7% to 92.48%. In addition, the time cost for annotating each sentence reduce from 10 to 3 minutes. The results indicate that proposed automatic annotation system is practical, and there is also a room for further improvement.