光谱图
倒谱
次谐波
语音识别
计算机科学
声学
非线性系统
物理
量子力学
作者
Itsuki Kitayama,Kiyohito Hosokawa,Shinobu Iwaki,Misao Yoshida,Akira Miyauchi,Makoto Ogawa,Hidenori Inohara
标识
DOI:10.1016/j.jvoice.2023.12.002
摘要
Hoarseness is primarily perceived as breathiness or roughness. Despite the various tools that quantitatively assess hoarseness, roughness has been difficult to quantify because of its complex acoustic structure, such as subharmonics. The parameter obtained from the two-stage cepstral analysis is promising for evaluating roughness. Thus, this study aimed to improve the accuracy of the parameter using a customized pitch setting and investigate the relationship between roughness and subharmonics.The design is a retrospective study.Two-stage cepstral analysis was used to analyze the voice recordings of 455 participants, speech impaired and normal controls, using the Analysis of Dysphonia in Speech and Voice and Praat software. For validation, the ground truth of subharmonics was visually quantified using a narrowband spectrogram. The reliability and validity of the two-stage cepstral analysis and subharmonics measures on spectrograms were evaluated.The two-stage cepstral analysis showed a very strong correlation (r = 0.963) between the two software programs. Intra- and inter-rater reliability of the subharmonics measures on spectrograms were also good. Two-stage cepstral analysis showed that even with customized pitch settings, the diagnostic systems and correlations for perceptual roughness and subharmonics were weak to moderate. The subharmonics measures on spectrograms showed a strong correlation with roughness and moderate diagnostic accuracy of subharmonics.The two-stage cepstral analysis showed some improvement in diagnostic accuracy and correlation with customized pitch settings, but it did not sufficiently detect subharmonics or roughness. The analysis using subharmonics measures on spectrograms proved the high correlation between subharmonics and roughness, indicating that developing acoustic analysis parameters that sufficiently detect subharmonics is necessary.
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