Repetitive Voice Evaluation in Dysphonic Teachers: Office Versus Home

Can Smartphones Be Used to Record Children's Voices for Acoustic Analysis?

OBJECTIVES

While technological advancements have enabled the utilization of smartphones for acoustic voice analysis, existing studies have predominantly focused on the adult population. However, dysphonia is prevalent in children, and their anatomy and physiology are different from those of adults. Thus, this paper aims to investigate the feasibility of using smartphones to record children's voices for acoustic voice analysis.

STUDY DESIGN

A methodological study.

METHODS

This study involved 29 children, aged 4-10 years, who had healthy voices. Voice recordings of sustained phonation and reading a sentence were obtained using four devices (1-AKG Micromic C520 headset microphone connected to a computer with the computerized speech lab (CSL), 2-Samsung S9 Plus, 3-iPhone 13 Mini, and 4-Huawei Y9 Prime). Then, all the recorded voice samples were analyzed using CSL, examining a total of 13 acoustic parameters. Pearson correlation analysis, Bland-Altman analysis, and uncertainty of measurement analysis were conducted to assess consistency and agreement across devices.

RESULTS

The highest correlation and accuracy between the smartphone measurements and the reference recording system were found for the fundamental frequency (F0) (r > 0.90, P < 0.01) in both speech samples. For other parameters, limited reliability was observed; while some showed weak correlations, others had low accuracy and consistency. There were, however, moderate-to-excellent correlations for the most measurements and a nonsignificant bias according to the Bland-Altman analysis.

CONCLUSION

This study is the first to investigate the feasibility of using smartphones for acoustic voice analysis focusing specifically on children. The results indicate that smartphone voice recordings can be used to reliably measure F0. More research is needed to improve measurement reliability for other parameters. Nonetheless, the findings demonstrate the potential for smartphones to enable accessible and reliable voice assessment in the pediatric population.

The Efficacy of Voice Therapy via Hybrid Group Telepractice Program with Asynchronous Components for Primary School Teachers: A Pilot Study

PURPOSE

To determine the efficacy of a hybrid group telepractice program in voice therapy for primary school teachers.

METHOD

The participants, consisting of 12 teachers with voice disorders (three males and nine females), participated in 11 sessions of the telepractice program, divided into one training session on vocal hygiene, five practice sessions by themselves, and five group practice sessions in 5weeks. Data on the vocal handicap index (VHI) measure was obtained pre- and post-intervention. The voice analysis included fundamental frequency (local), jitter (local), shimmer (local), harmonic-to-noise ratio (local), and maximum phonation time assessed by Praat software.

RESULT

The VHI assessment revealed a statistically significant difference (P < 0.05) in the emotional domain. There was no statistically significant difference (P > 0.05) in physical, functional, and total scores. Both males and females had no statistically significant difference (P > 0.05) in mean fundamental frequency. However, there was a statistically significant difference (P < 0.05) in jitter (local), shimmer (local), harmonics-to-noise ratio (local), and the maximum phonation time.

CONCLUSION

The group telepractice program in voice therapy for primary school teachers was effective. It could be utilized for voice therapy to prevent voice disorder problems in teachers.

Voice Recognition and Evaluation of Vocal Music Based on Neural Network

Artistic voice is the artistic life of professional voice users. In the process of selecting and cultivating artistic performing talents, the evaluation of voice even occupies a very important position. Therefore, an appropriate evaluation of the artistic voice is crucial. With the development of art education, how to scientifically evaluate artistic voice training methods and fairly select artistic voice talents is an urgent need for objective evaluation of artistic voice. The current evaluation methods for artistic voices are time-consuming, laborious, and highly subjective. In the objective evaluation of artistic voice, the selection of evaluation acoustic parameters is very important. Attempt to extract the average energy, average frequency error, and average range error of singing voice by using speech analysis technology as the objective evaluation acoustic parameters, use neural network method to objectively evaluate the singing quality of artistic voice, and compare with the subjective evaluation of senior professional teachers. In this paper, voice analysis technology is used to extract the first formant, third formant, fundamental frequency, sound range, fundamental frequency perturbation, first formant perturbation, third formant perturbation, and average energy of singing acoustic parameters. By using BP neural network methods, the quality of singing was evaluated objectively and compared with the subjective evaluation of senior vocal professional teachers. The results show that the BP neural network method can accurately and objectively evaluate the quality of singing voice by using the evaluation parameters, which is helpful in scientifically guiding the selection and training of artistic voice talents.