基于概率质量函数的低声语音频谱增强

H. Sharifzadeh, I. Mcloughlin, Farzaneh Ahmadi
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引用次数: 5

摘要

耳语可以有效地用于手机上的安静和私人通信,也是耳鼻喉科患者在声音休息制度下的通信手段。从窃窃私语中重建自然发音的语音可以用于从通信到生物医学工程等不同科学领域的几种类型的应用。尽管这种技术有很多有用的应用,但迄今为止,从耳语中重建自然语音的研究工作相对较少。本文提出了新的频谱增强和形成峰平滑方法,目的是在重建过程中获得更自然的语音。提出的方法使用概率质量密度函数通过低语识别可靠的形成峰轨迹,并相应地应用声音修改。主观评价实验进行,并报告,以评估技术的性能。一种通过改进的CELP编解码器将耳语近乎实时转换为正常语音的方法已经在我们之前发表的工作中进行了讨论,本文提出的形成峰修改方法建立在此基础上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spectral Enhancement of Whispered Speech Based on Probability Mass Function
Whispered speech can be effectively used for quiet and private communications over mobile phones and is also the communication means for ENT patients under a regime of voice rest. The reconstruction of natural sounding speech from such whispers can be useful for several types of application across different scientific fields ranging from communications to biomedical engineering. Despite the useful applications for a such technology, the reconstruction of natural speech from whispers has received relatively little research effort to date. This paper presents novel methods for spectral enhancement and formant smoothing with the aim of attaining more natural sounding speech within the reconstruction process. The proposed approach uses a probability mass-density function to identify a reliable formant trajectory through whispers and apply vocal modifications accordingly. Subjective evaluation experiments were performed, and are reported, to assess the performance of the techniques. A method for the near real-time conversion of whispers to normal phonated speech through a modified CELP codec has been discussed in our previously published work which, the proposed formant modification approach in this paper builds upon.
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