Huang Andy, Falk Tiago H, Chan Wai-Yip, Parsa Vijay, Doyle Philip
Department of Electrical and Computer Engineering, Queen's University, Kingston, Ontario, Canada.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:6210-3. doi: 10.1109/IEMBS.2009.5334545.
Evaluation of the quality of tracheoesophageal (TE) speech using machines instead of human experts can enhance the voice rehabilitation process for patients who have undergone total laryngectomy and voice restoration. Towards the goal of devising a reference-free TE speech quality estimation algorithm, we investigate the efficacy of speech signal features that are used in standard telephone-speech quality assessment algorithms, in conjunction with a recently introduced speech modulation spectrum measure. Tests performed on two TE speech databases demonstrate that the modulation spectral measure and a subset of features in the standard ITU-T P.563 algorithm estimate TE speech quality with better correlation (up to 0.9) than previously proposed features.
使用机器而非人类专家来评估气管食管(TE)语音质量,可以改善全喉切除和语音恢复患者的语音康复过程。为了设计一种无参考的TE语音质量评估算法,我们研究了标准电话语音质量评估算法中使用的语音信号特征的有效性,并结合最近引入的语音调制谱测量方法。在两个TE语音数据库上进行的测试表明,与先前提出的特征相比,调制谱测量方法和标准ITU-T P.563算法中的一部分特征在估计TE语音质量方面具有更好的相关性(高达0.9)。