Nefeli Dourou

A head-related transfer function (HRTF) is a mathematical model that describes the acoustic path between a sound source and a listener’s ear. Using binaural synthesis techniques, HRTFs play a crucial role in creating immersive audio experiences through headphones or loudspeakers, using binaural synthesis techniques. HRTF measurements can be conducted either with standardised mannequins or with in-ear microphones on real subjects. However, various challenges arise in, for example, individual differences in head shape, pinnae geometry, and torso dimensions, as well as in the extensive number of measurements required for optimal audio immersion. To address these issues, numerous methods have been developed to generate new HRTFs from existing data or through computer simulations. This review paper provides an overview of the current approaches and technologies for generating, adapting, and optimising HRTFs, with a focus on physical modelling, anthropometric techniques, machine learning methods, interpolation strategies, and their practical applications.

The head-related transfer functions (HRTFs) describe the acoustic path transfer functions between sound sources in the free-field and the listener’s ear canal. They enable the evaluation of the sound perception of a human being and the creation of immersive virtual acoustic environments that can be reproduced over headphones or loudspeakers. HRTFs are strongly individual and they can be measured by in-ear microphones worn by real subjects. However, standardized HRTFs can also be measured using artificial head simulators which standardize the body dimensions. In this paper, a comparative analysis of HRTF measurement using in-ear microphones is presented. The results obtained with in-ear microphones are compared with the HRTFs measured with a standard head and torso simulator, investigating different positions of the microphones and of the sound source and employing two different types of microphones. Finally, the HRTFs of five real subjects are measured and compared with the ones measured by the microphones in the ear of a standard mannequin.

Using equalization to improve sound listening experience is a well-established topic among the audio society. Finding a general equalization curve is a difficult task because of spectral content influenced by the reproduction system (loudspeakers and room environment) and personal preference diversity. Listeners’ mood is said to be a factor that affects the individual equalization preference. In this study, the effect of a listener’s mood on equalization preference is tried to be investigated. Starting from an experiment with fifty-two listeners, considering five predefined equalization curves and a database of ten music excerpts, the relationship between listeners’ mood and preferred sound equalization has been studied. The main findings of this study showed that the “High-frequency boosting” equalization was the most preferred among participants. However, the “High-frequency boosting” preference of low-aroused people was slightly lower than the high aroused listeners, increasing the preference of the “Low-frequency boosting”.