<strong></strong><strong>Objective(s):</strong> The aim of this study is to explore if there is a correlation between the typical voice classification and the oropharyngeal and laryngeal morpho...<strong></strong><strong>Objective(s):</strong> The aim of this study is to explore if there is a correlation between the typical voice classification and the oropharyngeal and laryngeal morphology, using video laryngeal stroboscopy and cervical posterior-anterior radiography on professional singers in Greece. <strong>Methods:</strong> 55 professional singers (28 females: 7 sopranos, 12 mezzo-sopranos, and 9 contraltos;27 males: 8 tenors, 12 baritones and 7 basses) were recruited for this study. All participants underwent stroboscopic and cervical posterior-anterior radiographic imaging of their oral pharyngeal and laryngeal area. Additionally, the voice classification and features (e.g., height, weight) of individuals were correlated statistically. <strong>Results:</strong> Statistically significant correlations were observed between the VC of the participants with the Phonetic Area (PA) (r = −0.451, p = 0.001) and the VC with the Oral-pharyngeal Cavity (OPC) area (r = −0.402, p = 0.001) in the total sample. Specifically, in male singers, the PA and VC correlation was r = −0.319, p = 0.047, and the VC and OPC area was r = −0.328, p = 0.044. Likewise, in female singers, the PA area and VC and PA were r = −0.336, p = 0.041 and the OPC area and VC were r = −0.344, p = 0.039. The analysis confirmed no correlations between VC and height and body weight. <strong>Conclusions:</strong> The cervical posteroanterior radiography in conjunction with laryngeal stroboscopy provided new morphometric correlations of the VC of professional singers with their Oropharyngeal and Laryngeal Anatomy.展开更多
Unvoiced/voiced classification of speech is a challenging problem especially under conditions of low signal-to-noise ratio or the non-white-stationary noise environment. To solve this problem, an algorithm for speech ...Unvoiced/voiced classification of speech is a challenging problem especially under conditions of low signal-to-noise ratio or the non-white-stationary noise environment. To solve this problem, an algorithm for speech classification, and a technique for the estimation of palrwise magnitude frequency in voiced speech am proposed. By using third order spectrum of speech signal to remove noise, in this algorithm the least spectrum difference to get refined pitch and the max harmonic number is given. And this algorithm utilizes spectral envelope to estimate signal-to-noise ratio of speech harmonics. Speech classification, voicing probability, and harmonic parameters of the voiced frame can be obtained. Simulation results indicate that the proposed algorithm, under complicated background noise, especially Gaussian noise, can effectively classify speech in high accuracy for voicing probability and the voiced parameters.展开更多
文摘<strong></strong><strong>Objective(s):</strong> The aim of this study is to explore if there is a correlation between the typical voice classification and the oropharyngeal and laryngeal morphology, using video laryngeal stroboscopy and cervical posterior-anterior radiography on professional singers in Greece. <strong>Methods:</strong> 55 professional singers (28 females: 7 sopranos, 12 mezzo-sopranos, and 9 contraltos;27 males: 8 tenors, 12 baritones and 7 basses) were recruited for this study. All participants underwent stroboscopic and cervical posterior-anterior radiographic imaging of their oral pharyngeal and laryngeal area. Additionally, the voice classification and features (e.g., height, weight) of individuals were correlated statistically. <strong>Results:</strong> Statistically significant correlations were observed between the VC of the participants with the Phonetic Area (PA) (r = −0.451, p = 0.001) and the VC with the Oral-pharyngeal Cavity (OPC) area (r = −0.402, p = 0.001) in the total sample. Specifically, in male singers, the PA and VC correlation was r = −0.319, p = 0.047, and the VC and OPC area was r = −0.328, p = 0.044. Likewise, in female singers, the PA area and VC and PA were r = −0.336, p = 0.041 and the OPC area and VC were r = −0.344, p = 0.039. The analysis confirmed no correlations between VC and height and body weight. <strong>Conclusions:</strong> The cervical posteroanterior radiography in conjunction with laryngeal stroboscopy provided new morphometric correlations of the VC of professional singers with their Oropharyngeal and Laryngeal Anatomy.
文摘Unvoiced/voiced classification of speech is a challenging problem especially under conditions of low signal-to-noise ratio or the non-white-stationary noise environment. To solve this problem, an algorithm for speech classification, and a technique for the estimation of palrwise magnitude frequency in voiced speech am proposed. By using third order spectrum of speech signal to remove noise, in this algorithm the least spectrum difference to get refined pitch and the max harmonic number is given. And this algorithm utilizes spectral envelope to estimate signal-to-noise ratio of speech harmonics. Speech classification, voicing probability, and harmonic parameters of the voiced frame can be obtained. Simulation results indicate that the proposed algorithm, under complicated background noise, especially Gaussian noise, can effectively classify speech in high accuracy for voicing probability and the voiced parameters.
