A Proposal of Vibrato Feature to Reflect Magnitude of Fluctuation of Fundamental Frequency for Evaluation Similarity in Singing Voice

2017 ◽  
Vol 137 (12) ◽  
pp. 1607-1614
Author(s):  
Chifumi Suzuki ◽  
Hideki Banno ◽  
Kensaku Asahi ◽  
Masanori Morise
Keyword(s):  
Fundamental Frequency ◽  
Singing Voice

The usefulness of the acoustic and the capacity analysis of singing voice

2019 ◽  
Vol 73 (3) ◽  
pp. 16-25
Author(s):  
Joanna Nowosielska-Grygiel ◽  
Jurek Olszewski
Keyword(s):  
Treatment Group ◽  
Fundamental Frequency ◽  
Voice Quality ◽  
Control Group ◽  
Capacity Analysis ◽  
Efficiency Coefficient ◽  
Singing Voice ◽  
Average Value ◽  
The Military ◽  
Relative Period

Abstract Introduction: The aim of the study was to assess the acoustic and capacity analysis of singing voice using DiagnoScope Specialist software. Material and methods: The study was conducted in 120 adults subjects, including 74 women and 46 men aged 21-5, were divided into 3 groups: I -40 subjects (treatment group) – professional vocalists, II- 40 subjects (treatment group) – semiprofessional vocalists, III- 40 subjects (control group) – students of The Military Medical Faculty at Medical University of Lodz – nonsingers. The research methodology included: primary medical history, physical examination (otolaryngological), vdeolaryngoscopic examination, the GRBAS scale for subjective voice evaluation, diagnostic voice acoustic and capacity analysis using DiagnoScope Specialist software, survey on lifestyle patterns which may affect voice quality. Results: Average value of the fundamental frequency F0 was the highest in professional vocalists’ group was 316,46 Hz in women and 165,09 Hz in men, in semiprofessional vocalists’ group was accordingly 260,50 Hz and 149,26 Hz, in nonsingers’ group was accordingly 261,23 Hz and 159, 27 Hz. Average value of Jitter parameter in professional vocalists’ group was 0,30% in women and 0,54% in men, in semiprofessional vocalists’ group was accordingly 0,31% and 0,57%, in nonsingers’ group was 0,31% and 0,56%. Average value of Shimmer parameter in professional vocalists’ group was 3,27% in women and 3,75% in men, in semiprofessional vocalists’ group was accordingly 3,46% and 3,77%, in nonsingers’ group was 4,33% and 4,39%. Average value of NHR index in professional vocalists’ group was 3,28% in women and 6,00% in men, in semiprofessional vocalists’ group was accordingly 3,23% and 6,72%, in nonsingers’ group was 3,89% and 6,13%. Conclusions: Values of the parameters which are measuring the character of the voice, relative period-to-period fundamental frequency perturbations, relative period-to-period amplitude perturbation and level of buzzing together with other methods have diagnostic and predictive value in early detection of voice disorders. Capacity analysis in singing voice showed very low values of the following parameters: phonation time, true phonation time, no phonation coefficient, voice efficiency coefficient and voice capacity. Key words: The acoustic and capacity analysis, singing voice

Perception of a Sung Vowel as a Function of Frequency-Modulation Rate and Excursion in Listeners With Normal Hearing and Hearing Impairment

2014 ◽  
Vol 57 (5) ◽  
pp. 1961-1971
Author(s):  
Marianna Vatti ◽  
Sébastien Santurette ◽  
Niels Henrik Pontoppidan ◽  
Torsten Dau
Keyword(s):  
Hearing Loss ◽  
Individual Differences ◽  
Hearing Impairment ◽  
Fundamental Frequency ◽  
Frequency Modulation ◽  
Normal Hearing ◽  
Musical Experience ◽  
Singing Voice ◽  
Modulation Rate ◽  
Frequency Changes

Purpose Frequency fluctuations in human voices can usually be described as coherent frequency modulation (FM). As listeners with hearing impairment (HI listeners) are typically less sensitive to FM than listeners with normal hearing (NH listeners), this study investigated whether hearing loss affects the perception of a sung vowel based on FM cues. Method Vibrato maps were obtained in 14 NH and 12 HI listeners with different degrees of musical experience. The FM rate and FM excursion of a synthesized vowel, to which coherent FM was applied, were adjusted until a singing voice emerged. Results In NH listeners, adding FM to the steady vowel components produced perception of a singing voice for FM rates between 4.1 and 7.5 Hz and FM excursions between 17 and 83 cents on average. In contrast, HI listeners showed substantially broader vibrato maps. Individual differences in map boundaries were, overall, not correlated with audibility or frequency selectivity at the vowel fundamental frequency, with no clear effect of musical experience. Conclusion Overall, it was shown that hearing loss affects the perception of a sung vowel based on FM-rate and FM-excursion cues, possibly due to deficits in FM detection or discrimination or to a degraded ability to follow the rate of frequency changes.

scholarly journals Vocal Melody Extraction via HRNet-Based Singing Voice Separation and Encoder-Decoder-Based F0 Estimation

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 298
Author(s):  
Yongwei Gao ◽  
Xulong Zhang ◽  
Wei Li
Keyword(s):  
Information Retrieval ◽  
High Resolution ◽  
Fundamental Frequency ◽  
State Of The Art ◽  
Main Difficulty ◽  
Harmonic Structure ◽  
Singing Voice ◽  
Pitch Estimation ◽  
Music Information ◽  
Singing Voice Separation

Vocal melody extraction is an important and challenging task in music information retrieval. One main difficulty is that, most of the time, various instruments and singing voices are mixed according to harmonic structure, making it hard to identify the fundamental frequency (F0) of a singing voice. Therefore, reducing the interference of accompaniment is beneficial to pitch estimation of the singing voice. In this paper, we first adopted a high-resolution network (HRNet) to separate vocals from polyphonic music, then designed an encoder-decoder network to estimate the vocal F0 values. Experiment results demonstrate that the effectiveness of the HRNet-based singing voice separation method in reducing the interference of accompaniment on the extraction of vocal melody, and the proposed vocal melody extraction (VME) system outperforms other state-of-the-art algorithms in most cases.

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