HRTF database at FIU DSP Lab

Gupta, Navarun; Barreto, Armando; Joshi, Manan; Agudelo, Juan Carlos

doi:10.1109/icassp.2010.5496084

Cited by 24 publications

(12 citation statements)

References 2 publications

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“…For the subjects, the DB contains anthropometric measurements, Statistics of anthropometric parameters and correlations between anthropometry and some temporal and spectral features of the HRTFs are reported. Simlar to Algazi's HRTF DB, Gupta et al [9] also developed the HRTF DB to provide more detail pinnae information such as the concha volume, concha area, and helix length. Gribonval et al [8] developed the evaluation algorithm enabling to compare the 3D audio sources with filtered sources by applying Sourceto-Distortion-Ratio (SDR), Source to-Interference-Ratio (SIR), and Source to-ArtifactRatio (SAR).…”

Section: Related Workmentioning

confidence: 98%

Design of database for evaluating 3D audio core algorithms

Kang

Hwang

Kim

et al. 2015

Multimed Tools Appl

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In this paper, we develop 3D audio evaluation database (DB) for verifying performance of new developed 3D audio core algorithms such as sound source localization, artificial reverberation, source separation, and crosstalk cancellation. Our system is designed to evaluate the 3D audio core algorithms automatically. Conventional evaluation DBs have to be executed manually for evaluating audio systems because the audio sources are not indexed in general.To solve this problem, we propose the architecture of 3D audio core algorithm evaluation database using database management system (DBMS). In the experimental section, we show feasibility of our system using real 3D sound sources for sound source separation algorithm.

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Section: Related Workmentioning

confidence: 98%

Design of database for evaluating 3D audio core algorithms

Kang

Hwang

Kim

et al. 2015

Multimed Tools Appl

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“…Due to the different characteristics and measurement methods of the databases, it was decided that the analysis of ITD asymmetry would be preformed separately and independently for each dataset. The four selected datasets are: LISTEN [9], CIPIC [10], FIU [11] and MARL [12].…”

Section: Databasesmentioning

confidence: 99%

“…The Florida International University DSP Lab measured the individual HRTFs of 15 different subjects 2 at 12 azimuth locations (30°spacing) and 6 elevations [11]. Recordings were conducted at 96 kHz and were accompanied by anthropometric data measured via a 3D scan of the pinnae.…”

Section: Fiu Databasementioning

confidence: 99%

Investigation of ITD Symmetry in Measured HRIRs

Genovese

Juras²,

Miller³

et al. 2016

Proceedings of the 22nd International Conference on Auditory Display - ICAD 2016

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The Interaural Time Difference is one of the primary localiza- tion cues for 3D sound. However, due to differences in head and ear anthropometry across the population, ITDs related to a sound source at a given location around the head will differ from sub- ject to subject. Furthermore, most individuals do not possess sym- metrical traits between the left and right pinnae. This fact may cause an angle-dependent ITD asymmetry between locations mir- rored across the left and right hemispheres. This paper describes an exploratory analysis performed on publicly available databases of individually measured HRIRs. The analysis was first performed separately for each dataset in order to explore the impact of dif- ferent formats and measurement techniques, and then on pooled sets of repositories, in order to obtain statistical information closer to the population values. Asymmetry in ITDs was found to be consistently more prominent in the rear-lateral angles (approxi- mately between 90° and 130° azimuth) across all databases inves- tigated, suggesting the presence of a sensitive region. A signifi- cant difference between the peak asymmetry values and the aver- age asymmetry across all angles was found on three out of four examined datasets. These results were further explored by pooling the datasets together, which revealed an asymmetry peak at 110° that also showed significance. Moreover, it was found that within the region of sensitivity the difference between specular ITDs ex- ceeds the just noticeable difference values for perceptual discrim- ination at all frequency bands. These findings validate the sta- tistical presence of ITD asymmetry in public datasets of individ- ual HRIRs and identify a significant, perceptually-relevant, region of increased asymmetry. Details of these results are of interest for HRIR modeling and personalization techniques, which should consider implementing compensation for asymmetric ITDs when aiming for perceptually accurate binaural displays. This work is part of a larger study aimed at binaural-audio personalization and user-characterization through non-invasive techniques.

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“…Acoustic measurement and numerical simulation are two primary approaches to obtain individualized HRTFs accurately [5][6][7][8][9][10][11]. However, acoustic measurement is time-consuming and requires a special apparatus; the calculation suffers from high requirements for computer performance and the scanning of physiological structures.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Algorithm for Predicting Median-Plane Head-Related Transfer Functions from Anthropometric Measurements

2019

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Since head-related transfer functions (HRTFs) represent the interactions between sounds and physiological structures of listeners, anthropometric parameters represent a straightforward way to customize (or predict) individualized HRTFs. This paper proposes a hybrid algorithm for predicting median-plane individualized HRTFs using anthropometric parameters. The proposed hybrid algorithm consists of three parts: decomposition of HRTFs; selection of key anthropometric parameters; and establishing a prediction formula. Firstly, an independent component analysis (ICA) is applied to median-plane HRTFs from multiple subjects to obtain independent components and subject-dependent weight coefficients. Then, a factor analysis is used to select key anthropometric parameters relevant to HRTFs. Finally, a regression formula that connects ICA weight coefficients to key anthropometric parameters is established by a multiple linear regression. Further, the effectiveness of the proposed hybrid algorithm is verified by an objective evaluation via spectral distortion and a subjective localization experiment. The results show that, when compared with generic Knowles Electronics Manikin for Acoustic Research (KEMAR) HRTFs, the spectral characteristics of the predicted HRTFs are closer to those of the individualized HRTFs. Moreover, the predicted HRTFs can alleviate front-back and up-down confusion and improve the accuracy of localization for most subjects.

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HRTF database at FIU DSP Lab

Cited by 24 publications

References 2 publications

Design of database for evaluating 3D audio core algorithms

Design of database for evaluating 3D audio core algorithms

Investigation of ITD Symmetry in Measured HRIRs

A Hybrid Algorithm for Predicting Median-Plane Head-Related Transfer Functions from Anthropometric Measurements

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