Poor Voice Quality in Future Elite Vocal Performers and Professional Voice Users

The voice quality of 86 occupational voice users, i.e., students of a high school for audiovisual communication, was assessed by means of a multidimensional test battery containing: the GRBAS scale, videolaryngostroboscopy, maximum phonation time, jitter, lowest intensity, highest frequency, dysphonia severity index (DSI), and voice handicap index (VHI). In a questionnaire on daily habits the prevalence of smoking, eating habits, and vocal abuse were recorded. A comparison of the voice characteristics of the future occupational voice users with a control group revealed significant differences. The results of the VHI and the DSI of these students revealed significantly worse scores than the score of a control group characterized by no vocal complaints. Moreover, the questionnaire on daily habits showed that the future elite vocal performers and professional voice users take less precautions for the care of their voices. These findings support the importance of a good balanced vocal coaching.     

Acoustic Analyses of Trained Singers Perceptually Identified from Speaking Samples

This study investigated selected acoustic cues in the speaking voices of five professional singers; cues that may have enabled na?ve listeners to differentiate them from nonsingers and other trained singers who were not consistently identified from their speaking voices. Subjects were divided into three groups based on listeners' perceptual judgments. Group I, the identified singers, consisted of five professional singers, three males and two females, with an average identification score, from their speaking utterances, of 79%. Group II, the unidentified singers, consisted of 15 trained singers, seven males and eight females, who, as a group, were identified correctly from their speaking utterances only 52% of the time. Group III consisted of 20 nonsingers who were incorrectly identified from their speaking utterances as singers only 36% of the time, that is, they were correctly identified as nonsingers from their speech 64% of the time. Acoustic parameters chosen for measurement from vowel productions were: (1) percent jitter, (2) percent shimmer, and (3) noise-to-harmonic ratio. The second sentence of the "Rainbow Passage" was selected to compare several frequency and duration measures between the three groups. These were: (1) mean speaking fundamental frequency, (2) standard deviation of the fundamental frequency, (3) sentence duration, (4) word duration, and (5) consonant/vowel ratio. The data indicated that the acoustic parameters that most consistently distinguished the identified singers from the unidentified singers and the nonsingers were fundamental frequency variation and durational differences. The identified singers varied their speaking fundamental frequency significantly more than did both the unidentified singers and the nonsingers. The identified singers also had longer vocalic segments than did the others.     

Resonance strategies for the belting style: Results of a single female subject study

This study explores resonance strategies used for the belting style and associated vocal fold vibratory patterns, for the vowels /e/, /a/, /i/, and /u/ on G4 and B4-flat. Acoustic spectra of belted vowels and their unoptimized, "speech-like" equivalents were compared. Vocal fold vibratory patterns were quantified using electroglottography. Results show that /a/ is inherently suitable for belting and requires no adjustment. For /e/, F2-H5 tuning was observed. For /i/, F1 was detuned from H1, enhancing also H2. For /u/, both F1 and F2 were raised to accomplish F2-H3 tuning. These results show that the loud, bright sound of the belting style is achieved by the implementation of resonance strategies that enhance higher harmonics. Electroglottography revealed that resonance strategies also result in raising the closed quotient (CQ) above 52%, an apparent threshold value for belting.     

应用ResNet和CatBoost检测重放语声*

针对短语声指令声频信息少、不适用句子级重放语声检测的问题以及近距离录声后用高质量重放设备重放的语声难以检测的问题，提出了一种适用于词级重放语声检测的模型。首先，利用短时傅里叶变换、低频平均能量计算和帧排序等方法选择声频帧，然后提取这些帧的伽马通频率倒谱系数。其次，用基于自注意机制的残差网络模型进一步提取伽马通频率倒谱系数中的信息，并转化为特征向量。最后，将提取后的特征向量用CatBoost分类，从而提高检测性能。在POCO数据集上的实验结果表明，提出的方法可以以87.54%的准确率和12.53%的等错误率检测重放语声，优于基线和现有的方法。该文提出的方法在ASVspoof2019 PA数据集上的等错误率与串联检测代价函数分别为4.92%和0.1418，证明该文方法也适用于多种设置的重放语声检测。