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Prosodic word boundary detection from Bengali continuous speech
Language Resources and Evaluation ( IF 2.7 ) Pub Date : 2019-11-13 , DOI: 10.1007/s10579-019-09478-0 Tanmay Bhowmik , Shyamal Kumar Das Mandal
Language Resources and Evaluation ( IF 2.7 ) Pub Date : 2019-11-13 , DOI: 10.1007/s10579-019-09478-0 Tanmay Bhowmik , Shyamal Kumar Das Mandal
Detection of word boundaries in continuous speech is a tedious process due to the absence of a definite pause or silence in the word boundary position. Thus, continuous speech recognition is a very challenging task. However, the prosodic word boundaries, unlike the written word boundaries, can be predicted using the prosodic parameters of continuous speech. This paper proposes a method for detecting such prosodic word boundaries from Bengali continuous speech. Bengali is a bound-stress language, where stress is observed on the first syllable of a prosodic word. Empirical Mode Decomposition is applied to the logarithm of fundamental frequency (F0) contour of continuous speech to detect prosodic word boundaries. 200 Bengali readout sentences, read by ten speakers, are analyzed for the present work. An overall prosodic boundary detection accuracy of 88.05% is achieved, whereas precision and recall values are 90.73% and 88.31%, respectively, with f-score as 89.5. A prosodic word dictionary comprising 5031 prosodic words has been developed by analyzing 1526 Bengali sentences with the proposed prosodic word boundary detection method.
中文翻译:
孟加拉语连续语音的韵律词边界检测
由于单词边界位置中没有确定的停顿或沉默,连续语音中单词边界的检测是一个繁琐的过程。因此,连续语音识别是一项非常具有挑战性的任务。但是,与书面单词边界不同,可以使用连续语音的韵律参数来预测韵律单词边界。本文提出了一种从孟加拉语连续语音中检测此类韵律词边界的方法。孟加拉语是一种重读重音语言,在重音词的第一个音节上会观察到重音。经验模态分解应用于基频(F 0)连续语音的轮廓以检测韵律词边界。分析了十位演讲者朗读的200个孟加拉语朗诵句子,用于本工作。总体韵律边界检测精度达到88.05%,而精度和查全率分别为90.73%和88.31%,f得分为89.5。通过使用提出的韵律词边界检测方法分析1526个孟加拉语句子,已经开发出了包含5031个韵律词的韵律词字典。
更新日期:2019-11-13
中文翻译:
孟加拉语连续语音的韵律词边界检测
由于单词边界位置中没有确定的停顿或沉默,连续语音中单词边界的检测是一个繁琐的过程。因此,连续语音识别是一项非常具有挑战性的任务。但是,与书面单词边界不同,可以使用连续语音的韵律参数来预测韵律单词边界。本文提出了一种从孟加拉语连续语音中检测此类韵律词边界的方法。孟加拉语是一种重读重音语言,在重音词的第一个音节上会观察到重音。经验模态分解应用于基频(F 0)连续语音的轮廓以检测韵律词边界。分析了十位演讲者朗读的200个孟加拉语朗诵句子,用于本工作。总体韵律边界检测精度达到88.05%,而精度和查全率分别为90.73%和88.31%,f得分为89.5。通过使用提出的韵律词边界检测方法分析1526个孟加拉语句子,已经开发出了包含5031个韵律词的韵律词字典。