An Automatic Speech Segmentation Algorithm of Portuguese based on Spectrogram Windowing

Lap-Man Hoi, Yuqi Sun, S. Im
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Abstract

Sentence segmentation is important for improving the human readability of Automatic Speech Recognition (ASR) systems. Although it has been explored through numerous interdisciplinary studies, segmentation of Portuguese is still time-consuming due to the lack of efficient automatic segmentation methods and the reliance on qualified phonetic experts. This paper presents a novel algorithm that efficiently segments speech into sentences by learning the spectrogram of sentences through windows using a classification model developed with an Artificial Neural Network (ANN). Based on our experiments, the beginning part of a European Portuguese (EP) sentence enables better identification of the sentence's boundaries. In addition, a window frame of spectrogram constructed by the previous ending of 100 milliseconds (ms) and the subsequent beginning of 300 ms presents the best performance in the automatic sentence segmentation. As a result, the proposed algorithm can automatically segment Portuguese speech into sentences by analyzing its spectrogram without knowing the speech semantics.
基于谱图窗的葡萄牙语自动语音分割算法
句子切分对于提高自动语音识别系统的可读性具有重要意义。尽管已经进行了许多跨学科的研究,但由于缺乏有效的自动分词方法和依赖于合格的语音专家,葡萄牙语的分词仍然是耗时的。本文提出了一种基于人工神经网络(ANN)的分类模型,通过窗口学习句子的谱图,有效地将语音分割成句子的算法。根据我们的实验,欧洲葡萄牙语(EP)句子的开头部分可以更好地识别句子的边界。另外,以前一个100毫秒(ms)结束和后一个300毫秒(ms)开始构建的谱图窗口框架在自动句子分割中表现出最好的性能。结果表明,该算法可以在不知道语音语义的情况下,通过分析葡萄牙语语音的谱图,自动将葡萄牙语语音分割成句子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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