We present a simulation method for the auralization of the ancient Greek double-reed wind instrument Aulos. The implementation is based on Digital Signal Processing and physical modeling techniques for the instrument's two parts: the excitation mechanism and the acoustic resonator with toneholes. Single-reeded instruments are in-depth studied firstly because their excitation mechanism is the one used in a great amount of modern wind-reed instruments and secondly because the physics governing the phenomena is less complicated than the double-reeded instruments. We here provide a detailed model of a system comprised of a double-reed linked to an acoustic resonator with toneholes to sonify Aulos. We validate our results by comparing our method's synthesized signal with recordings from a replica of Aulos of Poseidonia built in our lab. The comparison showed that the fundamental frequencies and the first three odd harmonics of the signals differ 6, 5, 3, and 2 cents on average, respectively, which is below the Just Noticeable Difference threshold.

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.

Operatic singing, traditionally taught through empirical and subjective methods, demands innovative approaches to enhance its pedagogical effectiveness today. This paper introduces a novel integration of advanced skeletal tracking technology into a prototype framework for operatic singing pedagogy research. Using the Microsoft Kinect Azure DK sensor, this prototype extracts detailed data on spinal, cervical, and shoulder alignment and movement data, with the aim of quantifying biomechanical movements during vocal performance. Preliminary results confirmed high face validity and biomechanical relevance. The incorporation of skeletal-tracking technology into vocal pedagogy research could help clarify certain technical aspects of singing and enhance sensorimotor feedback for the training of operatic singers.

This study explores the relationship between formant frequencies and the directivity patterns of the Greek singing voice. Recordings were conducted in a controlled acoustic environment with four professional singers, two trained in classical music and two in Byzantine chant. Using microphones placed symmetrically on a hemispherical structure, participants sang the Greek vowels across different registers. Directivity patterns were analyzed in third-octave bands centered on each singer’s first three formant frequencies (F1, F2, F3). The results indicate that directivity patterns vary with register and center frequency, with differences observed across vowels and singers. These findings contribute to vocal production research and the development of simulation, auralization, and virtual reality applications for speech and music.

Cicada chorus is one of the most characteristic continuous sounds that dominates the Greek soundscape during summer. In this paper, we will try to underline the importance of the Cicada singing from a double view: first we will go through a short reference on the meaning of this fascinating song of cicada through the myths of Esope and the writings of Aristotle and Plato, as cicada singing is ancient polyvalent symbol of resurrection and spiritual ecstasy. Then, being based on recent scientific researches on the acoustic behavior of the cicada according the natural conditions in different Greek landscape we will focus on the “eternal” cicadas chorus in the present landscape of Plato Academy during summer, by presenting the acoustic model of their "music" behavior.