Objective Identification of Prepubertal Female Singers and Non-singers by Singing Power Ratio Using Matlab

Usha, M.; Geetha, Y. V.; Darshan, Y.S.

doi:10.1016/j.jvoice.2016.06.016

Cited by 8 publications

(3 citation statements)

References 5 publications

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“…These skills are often developed as a result of training and singing experience, thereby creating a distinction in physiological, acoustic, and perceptual parameters of the voices of singers compared with that of non-singers. [3,4] The process of singing needs voice modulation which involves training of vocal muscles, vocal cords and other structures and systems involved in the production of voice. [4] It also needs a perfect coordination of brain and body.…”

Section: Introductionmentioning

confidence: 99%

Bhramari Pranayama - A Unique Voice Culturing Technique

Amrutha¹,

S²,

Jayakumar

2023

Int J Ayu Pharm Res

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A good voice is the basic need of humans. For professional voice users, voice governs their livelihood and social attraction. A good singing voice is attained by the regular vocal exercises and vocal training. Singing involves the skills like respiration, phonation, resonance and articulation. Bhramari Pranayama (BP) involves both humming and respiration. Humming is the resultant of the activity vocal structures which may have effect on the quality of the voice. Aim: To evaluate the effect of Bhramari Pranayama (BP) on voice quality Settings and Design: The study is an open clinical trial involving 30 healthy prospective singers fulfilling the inclusion and exclusion criteria, consenting for the study, who were enrolled through a survey in music schools in the region of Belagavi, Karnataka. Methods and Material: The voice of the 30 healthy prospective singers was recorded using PRAAT software with standard vocal tasks on day 0 of the study. Participants practiced 21 cycles of Bhramari Pranayama in the morning for 30 days. On Day 30, after the practice the voice was re-recorded with same vocal tasks and standard operative procedures being maintained. The recorded voice samples were saved and were subjected for voice analysis using softwares PRAAT, Vaghmi, CSL at AIISH, Mysuru. Statistical analysis used: Statistical analysis was done using SPSS 21 and Paired ‘t’ test was applied to derive the results. Statistical Significance was set up at p<0.05. Results: Bhramari pranayama showed highly significant results in the root mean square values of the Singing power ratio - SPR (p<0.01) and singing power difference (p<0.01). Significant results in the lowest value of the singing amplitude (p<0.05), singing amplitude range (p<0.01) and mean formant frequency of second formant of vowel /u/(p<0.05). Conclusion: Bhramari Pranayama improved the resonance characteristics of the voice and there by improved the quality of singing voice in prospective singers.

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Section: Introductionmentioning

confidence: 99%

Bhramari Pranayama - A Unique Voice Culturing Technique

Amrutha¹,

S²,

Jayakumar

2023

Int J Ayu Pharm Res

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“…In particular, it has been reported that the sound spectra of well-trained male opera singers exhibit a significant peak at about 3 kHz, which is absent in untrained singers [2]. This spectral peak is called the singer's formant; it has been analyzed with spectral modeling synthesis and has been issued as the singing power ratio [3][4][5][6] or quality ratio [7].…”

Section: Introductionmentioning

confidence: 99%

Mechanical classification of voice quality

Yoshida¹,

Shinomoto²

2020

Preprint

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While there is no a priori definition of good singing voices, we tend to make consistent evaluations of the quality of singing almost instantaneously. Such an instantaneous evaluation might be based on the sound spectrum that can be perceived in a short time. Here we devise a Bayesian algorithm that learns to evaluate the choral proficiency, musical scale, and gender of individual singers using the sound spectra of singing voices. In particular, the classification is performed on a set of sound spectral intensities, whose frequencies are selected by minimizing the Bayes risk. This optimization allows the algorithm to capture sound frequencies that are essential for each discrimination task, resulting in a good assessment performance. Experimental results revealed that a sound duration of about 0.1 sec is sufficient for determining the choral proficiency and gender of a singer. With a program constructed on this algorithm, everyone can evaluate choral voices of others and perform private vocal exercises.

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“…The idea of using voice recognition in biometric systems is shown in [6]. Interesting approach to analysis of sound is shown in [7], where the system identifies singer based on power of sound. Another approach is to use acoustic-spectrographic action in these field what was introduced in [8].…”

Section: Introductionmentioning

confidence: 99%

Voice recognition through the use of Gabor transform and heuristic algorithm

Woźniak

Połap

2017

International Journal of Electronics and Telecommunications

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Abstract-Increasingly popular use of verification methods based on specific characteristics of people like eyeball, fingerprint or voice makes inventing more accurate and irrefutable methods of that urgent. In this work we present voice verification based on Gabor transformation. Proposed approach involves creation of spectrogram, which serves as a habitat for the population in selected heuristic algorithm. The use of heuristic allows for feature extraction to enable identity verification using classical neural network. The results of the research are presented and discussed to show efficiency of the proposed methodology.

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Objective Identification of Prepubertal Female Singers and Non-singers by Singing Power Ratio Using Matlab

Cited by 8 publications

References 5 publications

Bhramari Pranayama - A Unique Voice Culturing Technique

Bhramari Pranayama - A Unique Voice Culturing Technique

Mechanical classification of voice quality

Voice recognition through the use of Gabor transform and heuristic algorithm

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