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Voice and Speech Assessment From Telephone Recordings Using Prosodic Analysis Based on μ-Law-Companded Features

机译:基于μ-法律分析的韵律分析的电话录制语音和语音评估

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Objective assessment of voice and speech properties via telephone is desirable for rehabilitation purposes. 82 patients after partial laryngectomy read a standardized text on the phone. Five experienced raters assessed speech effort, match of breath and sense units, vocal tone, intelligibility, and overall voice quality perceptually based on these recordings. Objective evaluation was performed by the word accuracy and word correctness of a speech recognition system, and a set of prosodic features. The speech recognition system used μ-law features, i. e. modified Mel-Frequency Cepstrum Coefficients (MFCCs). The prosodic features were computed based on word hypotheses graphs produced by the speech recognizer. The human-machine correlation between these features and the perceptual evaluation show slightly better results for the system based on μ-law features than for the baseline MFCC system.
机译:通过电话的客观评估语音和语音特性是可取的康复目的。部分喉部切除术后82名患者在手机上阅读标准化文本。五位经验丰富的评估者评估了言语努力,呼吸和感知单位,声音,可懂度和整体语音质量的匹配基于这些录音。通过语音识别系统的单词精度和词正确性和一组韵律特征来执行客观评估。语音识别系统使用了μ-lave功能,i。 e。改性熔融频率综合系数(MFCC)。基于由语音识别器产生的单词假设图来计算韵律特征。这些特征与感知评估之间的人机相关性显示了基于μ-Lave特征的系统略微更好的结果,而不是基线MFCC系统。

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