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Effect of Individualized Head-Related Transfer Functions on Distance Perception in Virtual Reproduction for a Nearby Sound Source

Yu Guangzheng, Wang Liliang

Archives of Acoustics

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2019

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Vol. 44, No. 2

251--258

EN

The head-related transfer function (HRTF) is dependent on the position of the sound source (both direction and distance) and is also affected by individual anatomical parameters. Individualized HRTFs have been shown to affect the perception of sound direction, but have not been considered in distance perception. This work aims to discover, by means of psychoacoustic experiments for a virtual reproduction system through a pair of in-ear headphones, the effect of individualized HRTF on auditory distance perception for a nearby sound source. The individualized HRTFs of six subjects and the non-individualized HRTFs of a mannequin at seven distances between 0.2 and 1.0 m and five lateral azimuths between 45° and 135° in the horizontal plane were processed with white noise to generate binaural signals. Further, the individualized and non-individualized HRTFs were used in the auditory distance perception experiments. Results of distance perception show that the variance of distance perception results among subjects is significant, the reason could be the stimuli are lack of dynamic cue and early reflections, or the audi tory difference of distance perception among subjects. However, via the analyses of mean slope of perceptual distance and correlation between the perceptual and real distance, we find that the individualized HRTF cue has insignificant influence on distance perception.

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Head-Related Transfer Function Selection Using Neural Networks

Yao S.-N., Collins T., Liang C.

Archives of Acoustics

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2017

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Vol. 42, No. 3

365--373

EN

In binaural audio systems, for an optimal virtual acoustic space a set of head-related transfer functions (HRTFs) should be used that closely matches the listener’s ones. This study aims to select the most appropriate HRTF dataset from a large database for users without the need for extensive listening tests. Currently, there is no way to reliably reduce the number of datasets to a smaller, more manageable number without risking discarding potentially good matches. A neural network that estimates the appropriateness of HRTF datasets based on input vectors of anthropometric measurements is proposed. The shapes and sizes of listeners’ heads and pinnas were measured using digital photography; the measured anthropometric parameters form the feature vectors used by the neural network. A graphical user interface (GUI) was developed for participants to listen to music transformed using different HRTFs and to evaluate the fitness of each HRTF dataset. The listening scores recorded were the target outputs used to train the neural networks. The aim was to learn a mapping between anthropometric parameters and listener’s perception scores. Experimental validations were performed on 30 subjects. It is demonstrated that the proposed system produces a much more reliable HRTF selection than previously used methods.

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Subjective Evaluation of Three Headphone-Based Virtual Sound Source Positioning Methods Including Differential Head-Related Transfer Function

Storek D., Rund F., Marsalek P.

Archives of Acoustics

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2016

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Vol. 41, No. 3

437--447

EN

This paper analyses the performance of Differential Head-Related Transfer Function (DHRTF), an alternative transfer function for headphone-based virtual sound source positioning within a horizontal plane. This experimental one-channel function is used to reduce processing and avoid timbre affection while preserving signal features important for sound localisation. The use of positioning algorithm employing the DHRTF is compared to two other common positioning methods: amplitude panning and HRTF processing. Results of theoretical comparison and quality assessment of the methods by subjective listening tests are presented. The tests focus on distinctive aspects of the positioning methods: spatial impression, timbre affection, and loudness fluctuations. The results show that the DHRTF positioning method is applicable with very promising performance; it avoids perceptible channel coloration that occurs within the HRTF method, and it delivers spatial impression more successfully than the simple amplitude panning method.