Singing Voice Detection: A Survey

Singing voice detection or vocal detection is a classification task that determines whether there is a singing voice in a given audio segment. This process is a crucial preprocessing step that can be used to improve the performance of other tasks such as automatic lyrics alignment, singing melody transcription, singing voice separation, vocal melody extraction, and many more. This paper presents a survey on the techniques of singing voice detection with a deep focus on state-of-the-art algorithms such as convolutional LSTM and GRU-RNN. It illustrates a comparison between existing methods for singing voice detection, mainly based on the Jamendo and RWC datasets. Long-term recurrent convolutional networks have reached impressive results on public datasets. The main goal of the present paper is to investigate both classical and state-of-the-art approaches to singing voice detection.

Fitness Training and the Singing Voice: Successful Strategies for Integration

With industry changes surrounding expectations of how singers appear in costume and move on stage, many singers integrate fitness training into their lifestyle as they use their bodies as instruments and as athletes. This article comes from both lived experience in fitness training while being a singer and the science that gov-erns the process of training. It examines safe ways for vocational singers to engage in fitness training without detriment to performance careers.

Can a natural singing voice be enhanced through digital processing? Implications of voice training and vocology in singers

Introduction. The traditional way of facilitating a good singing voice has been achieved through rigorous voice training. In the modern days, however, there are some aspects of the singing voice that can be enhanced through digital processing. Although in the past, the frequency or intensity manipulations had to be achieved through the various singing techniques of the singer, technology today allows the singing voice to be enhanced from the instruments within recording studios. In essence, the traditional voice pedagogy and the evolution of digital audio processing both strive to achieve a better quality of the singing voice, but with different methods. Nevertheless, the major aspects of how the singing voice can be manipulated are not communicated among the professionals in each field. Objective. This paper offers insights as to how the quality of the singing voice can be changed physiologically through the traditional ways of voice training, and also digitally through various instruments that are now available in recording studios. Reflection. The ways in which singers train their voice must be mediated with the audio technology that is available today. Although there are aspects in which the digital technology can aid the singer’s voice, there remain areas in which the singers must train their singing system in a physiological level to produce a better singing voice.

Singing Voice Therapy Revisited

Introduction. Singing is a type of sportive activity and, like sports medicine, professional voice medicine is interested in the habilitation and rehabilitation of the vocal performer. The vocal needs of the professional vocal performer may not be similar to other professional or non-professional voice users. Like a professional athlete, a vocal performer’s ability to perform for many decades at a high level will be enhanced by basing artistic and lifestyle decisions on a scientifically sound foundation. Objective. The aim of this study is to present a multidimensional introduction to the methods of SVT, incorporating the principles of sport and exercise medicine, and physical therapy and rehabilitation. Reflection. Singing voice therapy needs to provide answers to “what”, “why”, “how”, and “when” questions. SVT must first correctly identify the problem, leading to the “how to do” solutions for a wide variety of cases, followed by a schedule of prescribed activities including answers to the “why” question (which exercise relates to which muscle). The periodization and motor learning principles provide a temporal answer to the “when” question when developing habilitation and/or rehabilitative protocols. Conclusion. Singing is not only an artistic expression, but also a sportive performance. The clinical approach to professional voice is a multidimensional and multi-layered team effort. All practices are structured by blending scientific and pedagogical knowledge.

Exploring Channel Properties to Improve Singing Voice Detection with Convolutional Neural Networks

Singing voice detection is still a challenging task because the voice can be obscured by instruments having the same frequency band, and even the same timbre, produced by mimicking the mechanism of human singing. Because of the poor adaptability and complexity of feature engineering, there is a recent trend towards feature learning in which deep neural networks play the roles of feature extraction and classification. In this paper, we present two methods to explore the channel properties in the convolution neural network to improve the performance of singing voice detection by feature learning. First, channel attention learning is presented to measure the importance of a feature, in which two attention mechanisms are exploited, i.e., the scaled dot-product and squeeze-and-excitation. This method focuses on learning the importance of the feature map so that the neurons can place more attention on the more important feature maps. Second, the multi-scale representations are fed to the input channels, aiming at adding more information in terms of scale. Generally, different songs need different scales of a spectrogram to be represented, and multi-scale representations ensure the network can choose the best one for the task. In the experimental stage, we proved the effectiveness of the two methods based on three public datasets, with the accuracy performance increasing by up to 2.13 percent compared to its already high initial level.

Defining the Therapeutic Singing Voice: Further Examination of the Everyday Singing Practices of Music Therapists

Twelve music therapists were observed working clinically in 3 to 5 of their music therapy sessions and subsequently interviewed about their clinical work in order to further examine and define the essential characteristics of therapeutic singing in music therapy clinical practice. Observational and interview data were analyzed separately using procedures consistent with qualitative content analysis and then integrated to provide a comprehensive picture of these singing practices. Analysis of these data revealed 3 interrelated dimensions of therapeutic singing that were integrated into the larger realization of therapeutic singing: (1) foundational vocal skills, (2) vocal engagement, and (3) authenticity. Implications for the education and training of music therapy students, vocal health, and a reevaluation of the American Music Therapy Association’s competencies contextualize these findings for the profession as a whole.

PHYSIOLOGICAL VOCAL WARMING UP PROGRAM IN RELIGIOUS SINGERS

Purpose: To analyze the effectiveness of a physiological vocal warm-up program focused on religious singers. Method: longitudinal study involving 39 subjects male and female, aged at least 18 and at most 50, the participants underwent an evaluation vocal pre-warm-up and vocal post-warm-up, results being compared to both evaluations. The evaluation was applied questionnaire vocal habits and symptoms, acoustic analysis and auditory perceptual analysis. The study was conducted in Catholic Churches of Várzea Grande City in the state Mato Grosso. Results: They said participants to use the corner of a median of 87.3 months with weekly frequency of 2.4 times per week. However, 89.7% of the singers reported not warm up the voice before the corner and not desaquecerem 94.9% after the corner. In inadequate vocal habits most said talking aplenty. Already in vocal symptoms the three most prevalent were: voice worse in the morning (59.0%), loss of treble (54.4%) and hoarseness constant (51.3%). After application of vocal warm-up program improvement was observed in vocal self assessment and auditory perceptual analysis. There was also a significant increase in the fundamental frequency of the sustained vowel, but for the singing voice there was no change in acoustic parameters analyzed. Conclusion: The vocal heating program was effective with positive changes in voice adjustments, providing a more comfortable voice output this being noticed by singers themselves.

Towards a Singing Voice Multi-Sensor Analysis Tool: System Design, and Assessment Based on Vocal Breathiness

Singing voice is a human quality that requires the precise coordination of numerous kinetic functions and results in a perceptually variable auditory outcome. The use of multi-sensor systems can facilitate the study of correlations between the vocal mechanism kinetic functions and the voice output. This is directly relevant to vocal education, rehabilitation, and prevention of vocal health issues in educators; professionals; and students of singing, music, and acting. In this work, we present the initial design of a modular multi-sensor system for singing voice analysis, and describe its first assessment experiment on the ‘vocal breathiness’ qualitative characteristic. A system case study with two professional singers was conducted, utilizing signals from four sensors. Participants sung a protocol of vocal trials in various degrees of intended vocal breathiness. Their (i) vocal output, (ii) phonatory function, and (iii) respiratory behavior-per-condition were recorded through a condenser microphone (CM), an Electroglottograph (EGG), and thoracic and abdominal respiratory effort transducers (RET), respectively. Participants’ individual respiratory management strategies were studied through qualitative analysis of RET data. Microphone audio samples breathiness degree was rated perceptually, and correlation analysis was performed between sample ratings and parameters extracted from CM and EGG data. Smoothed Cepstral Peak Prominence (CPPS) and vocal folds’ Open Quotient (OQ), as computed with the Howard method (HOQ), demonstrated the higher correlation coefficients, when analyzed individually. DECOM method-computed OQ (DOQ) was also examined. Interestingly, the correlation coefficient of pitch difference between estimates from CM and EGG signals appeared to be (based on the Pearson correlation coefficient) statistically insignificant (a result that warrants investigation in larger populations). The study of multi-variate models revealed even higher correlation coefficients. Models studied were the Acoustic Breathiness Index (ABI) and the proposed multiple regression model CDH (CPPS, DOQ, and HOQ), which was attempted in order to combine analysis results from microphone and EGG signals. The model combination of ABI and the proposed CDH appeared to yield the highest correlation with perceptual breathiness ratings. Study results suggest potential for the use of a completed system version in vocal pedagogy and research, as the case study indicated system practicality, a number of pertinent correlations, and introduced topics with further research possibilities.