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Investigating Audio Perception: Precedence Effect, HRTFs, and Room Reverberation Models

This mid-term review by John W. Worley focuses on auditory perception principles within the context of the University of Patras’ Audio Group. It explores key topics such as the precedence effect, learning non-individualized Head-Related Transfer Functions (HRTFs), and perceptual models of room reverberation, relevant for speech recognition. The review assesses experimental results on auditory cues, the Franssen illusion, and perceptual factors influencing room responses. The findings aim to enhance understanding in multi-source auditory environments, contributing to advancing audio technology and research.

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Investigating Audio Perception: Precedence Effect, HRTFs, and Room Reverberation Models

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  1. Mid-Term Review John W. Worley AudioGroup, WCL Department of Electrical and Computer Engineering University of Patras, Greece http://www.wcl.ee.upatras.gr/AudioGroup/

  2. Tasks • 2.1 The precedence effect • Franssen illusion • 2.2 Reliability of auditory cues in multi-source scenarios • Learning non-individualised HRTFs • 2.3 Perceptual models of room reverberation with application to speech recognition • Complex smoothed room responses • Perceptual factors in room responses

  3. Task 2.1 Franssen illusion • Reverberant environments = cue to multiple directions. • The precedence effect = stable directional percept. • Franssen illusion (F.I.) • Precedence effect. • ITD/ILD dependant

  4. Task 2.1 Franssen illusion • Hypothesis • Localisation requires transients. • Signal spectral density. • Room differences. • ITD/ILD dependant. • Solution • Various onset transitions. • Sinusoid & Harmonic complex’s. • Large vs. small rooms • At present: • F.I. in reverberation chamber. • No transition effect. • Increasing spectral density = Increased localisability. • F.I. dependant on poor stimuli localisability. • Future: • F.I. with Grouping cues??

  5. Task 2.2 Learning non-individualised HRTFs Cone-of-confusion MVP HRTFs Individual HRTFs

  6. Type – I (2 listeners) Type - II (3 listeners) Task 2.2 Learning non-individualised HRTFs: Results • Response bias significantly determines reversal type = No reversal predisposition. = Majority of front-to-back reversals.

  7. Task 2.3 Complex Smoothing Room Impulse Response (RIR): time domain frequency domain Original RIR Smoothed RIR

  8. Start with a “smoothed” room response Use smoothing based on perception variable spectral resolution variable frequency-dependent windowing Employ “room masking models” perceptual smoothing profiles

  9. Task 2.3 Inverse filtering using smoothed filters time domain frequency domain modification compensation from:“Results for Room Acoustics Equalisation Based on Smoothed Responses”Panagiotis D. Hatziantoniou and John N. Mourjopoulos,114th AES Convention, Amsterdam, March 2003

  10. Task 2.3 Smoothed filters physical metrics Tests in 6 rooms of Volume 60m3 – 11000m3 • EDT reduced by up to 0,5 sec • C80 improves by up to 5 dB • D50 improves by up to 20% • Spectral deviation is reduced up to 4 dB from:“Results for Room Acoustics Equalisation Based on Smoothed Responses”Panagiotis D. Hatziantoniou and John N. Mourjopoulos, 114th AES Convention, Amsterdam, March 2003

  11. Task 2.3 Perceptual factors in room responses • Real-time perception test. • Various stimuli types (steady-state & transients). • Assess multiple perceptual factors.

  12. Task 2.3 Perceptual factors in room responses • Source width. • Source distance. • Envelopment.

  13. Task 2.3 Perceptual factors in room responses • Anchor end-points with illustrative demonstrations and explanation. • Results subjected to factor analysis

  14. Future work • Perceptual factors in room responses (2.3). • ITD/ILD plausibility cues (2.1, 2.2). • The combination of the cues is still debated. • Use F0 grouping with FI for hierarchy of cues (2.2).

  15. AudioGroup, WCL Department of Electrical and Computer Engineering University of Patras, Greece http://www.wcl.ee.upatras.gr/AudioGroup/

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