Subjective Assessments of Real-Time Room Dereverberation and Loudspeaker Equalisation Panagiotis Hatziantoniou and John Mourjopoulos AudioGroup, WCL Department.

Slides:



Advertisements
Similar presentations
David Griesinger Acoustics, Cambridge, Massachusetts, USA
Advertisements

ENF1104 Problem Solving for Engineers – Acoustic Project Reverberation Time Broad definition: Time taken for sound level in a room to reduce by 60 dB.
Basic Acoustics Inverse square law Reinforcement/cancellation
3-D Sound and Spatial Audio MUS_TECH 348. Wightman & Kistler (1989) Headphone simulation of free-field listening I. Stimulus synthesis II. Psychophysical.
ELEC 407 DSP Project Algorithmic Reverberation – A Hybrid Approach Combining Moorer’s reverberator with simulated room IR reflection modeling Will McFarland.
Vocal Emotion Recognition with Cochlear Implants Xin Luo, Qian-Jie Fu, John J. Galvin III Presentation By Archie Archibong.
PREDICTION OF ROOM ACOUSTICS PARAMETERS
Reduction of Additive Noise in the Digital Processing of Speech Avner Halevy AMSC 664 Final Presentation May 2009 Dr. Radu Balan Department of Mathematics.
Musical Sound Processing Student Name: 鄭建健
Chapter 4 Image Enhancement in the Frequency Domain.
Image Enhancement in the Frequency Domain Part III Dr. Samir H. Abdul-Jauwad Electrical Engineering Department King Fahd University of Petroleum & Minerals.
ICA Madrid 9/7/ Simulating distance cues in virtual reverberant environments Norbert Kopčo 1, Scott Santarelli, Virginia Best, and Barbara Shinn-Cunningham.
An Acoustical Study of the Salt Lake Tabernacle Sarah Rollins Timothy W. Leishman Acoustics Research Group Department of Physics and Astronomy Brigham.
Interrupted speech perception Su-Hyun Jin, Ph.D. University of Texas & Peggy B. Nelson, Ph.D. University of Minnesota.
Auditory Scene Analysis Ian Kaminskyj Electrical & Computer Systems Engineering, Monash University.
Hearing & Deafness (3) Auditory Localisation
SUBJECTIVE AND OBJECTIVE ROOM ACOUSTIC PARAMETERS Acoustics of Concert Halls and Rooms Science of Sound, Chapter 23 Concert Halls and Opera Houses (Beranek.
STUDIOS AND LISTENING ROOMS
Image Enhancement in the Frequency Domain Part II Dr. Samir H. Abdul-Jauwad Electrical Engineering Department King Fahd University of Petroleum & Minerals.
20 10 School of Electrical Engineering &Telecommunications UNSW UNSW 10 Author: Jonathan Jayanthakumar An Analysis of the Role of the First.
Cross-Spectral Channel Gap Detection in the Aging CBA Mouse Jason T. Moore, Paul D. Allen, James R. Ison Department of Brain & Cognitive Sciences, University.
Experimental Equalization of a One-Dimensional Sound Field Using Energy Density and a Parametric Equalizer Micah Shepherd, Xi Chen, Timothy W. Leishman,
Recent Research in Musical Timbre Perception James W. Beauchamp University of Illinois at Urbana-Champaign Andrew B. Horner Hong University of Science.
L INKWITZ L AB Accurate sound reproduction from two loudspeakers in a living room 13-Nov-07 (1) Siegfried Linkwitz.
1 A. Lipsky, N. Miteva, E. Lokshin Department of Electrical and Electronic Engineering Ariel University Center of Samaria Israel Electric Power Quality.
Introduction to Spectral Estimation
Acoustic Echo Cancellation Using Digital Signal Processing. Presented by :- A.Manigandan( ) B.Naveen Raj ( ) Parikshit Dujari ( )
Sub-band Mixing and Addition of Digital Effects for Consumer Audio ELECTRICAL & ELECTRONIC ENGINEERING FINAL YEAR PROJECTS 2012/2013 Presented by Fionn.
Normalization of the Speech Modulation Spectra for Robust Speech Recognition Xiong Xiao, Eng Siong Chng, and Haizhou Li Wen-Yi Chu Department of Computer.
Improved 3D Sound Delivered to Headphones Using Wavelets By Ozlem KALINLI EE-Systems University of Southern California December 4, 2003.
Dual-Channel FFT Analysis: A Presentation Prepared for Syn-Aud-Con: Test and Measurement Seminars Louisville, KY Aug , 2002.
Adaptive Design of Speech Sound Systems Randy Diehl In collaboration with Bjőrn Lindblom, Carl Creeger, Lori Holt, and Andrew Lotto.
Acoustic impulse response measurement using speech and music signals John Usher Barcelona Media – Innovation Centre | Av. Diagonal, 177, planta 9,
Reduction of Additive Noise in the Digital Processing of Speech Avner Halevy AMSC 663 Mid Year Progress Report December 2008 Professor Radu Balan 1.
WAVELET (Article Presentation) by : Tilottama Goswami Sources:
Supervisor: Dr. Boaz Rafaely Student: Limor Eger Dept. of Electrical and Computer Engineering, Ben-Gurion University Goal Directional analysis of sound.
Name : Arum Tri Iswari Purwanti NPM :
WP4 – Sound Object Identification WP5 – Enriched Access Tools.
Sounds in a reverberant room can interfere with the direct sound source. The normal hearing (NH) auditory system has a mechanism by which the echoes, or.
Authors: Sriram Ganapathy, Samuel Thomas, and Hynek Hermansky Temporal envelope compensation for robust phoneme recognition using modulation spectrum.
Recognition of Speech Using Representation in High-Dimensional Spaces University of Washington, Seattle, WA AT&T Labs (Retd), Florham Park, NJ Bishnu Atal.
Open-Loop Dereverberation of Multichannel Room Impulse Responses Bowon Lee, Mark A. Hasegawa-Johnson, and Camille Goudeseune Department of Electrical and.
Analysis of variance John W. Worley AudioGroup, WCL Department of Electrical and Computer Engineering University of Patras, Greece
Hearing Research Center
1 Cross-language evidence for three factors in speech perception Sandra Anacleto uOttawa.
Scaling Studies of Perceived Source Width Juha Merimaa Institut für Kommunikationsakustik Ruhr-Universität Bochum.
Listeners weighting of cues for lateral angle: The duplex theory of sound localization revisited E. A. MacPherson & J. C. Middlebrooks (2002) HST. 723.
Room Acoustics DHC 161 March 2, Early sound in a room.
The Relation Between Speech Intelligibility and The Complex Modulation Spectrum Steven Greenberg International Computer Science Institute 1947 Center Street,
On the improvement of virtual localization in vertical directions using HRTF synthesis and additional filtering Wersényi György SZÉCHENYI ISTVÁN UNIVERSITY,
Project-Final Presentation Blind Dereverberation Algorithm for Speech Signals Based on Multi-channel Linear Prediction Supervisor: Alexander Bertrand Authors:
ELECTRONIC SOUND SYSTEMS INTRODUCTION PRINCIPAL USES DESIGN FACTORS SYSTEM COMPONENTS LOUDSPEAKER ARRANGEMENTS DESCRIPTION: ELECTRONIC SYSTEM WHICH REINFORCES.
MINUET Musical Interference Unmixing Estimation Technique Scott Rickard, Conor Fearon Department of Electronic & Electrical Engineering University College.
SOME SIMPLE MANIPULATIONS OF SOUND USING DIGITAL SIGNAL PROCESSING Richard M. Stern demo January 15, 2015 Department of Electrical and Computer.
THE SIGNIFICANCE OF SOUND DIFFRACTION EFFECTS IN PREDICTING ACOUSTICS IN ANCIENT THEATRES Presented by : Panos Economou P.E. Mediterranean Acoustics Research.
SPATIAL HEARING Ability to locate the direction of a sound. Ability to locate the direction of a sound. Localization: In free field Localization: In free.
Predicting the Intelligibility of Cochlear-implant Vocoded Speech from Objective Quality Measure(2) Department of Electrical Engineering, The University.
Adv DSP Spring-2015 Lecture#11 Spectrum Estimation Parametric Methods.
Franssen illusion within large rooms John W. Worley AudioGroup, WCL Department of Electrical and Computer Engineering University of Patras, Greece
Auditory Localization in Rooms: Acoustic Analysis and Behavior
PREDICTION OF ROOM ACOUSTICS PARAMETERS
Auditorium acoustic (continued)
Mid-Term Review John W. Worley AudioGroup, WCL
ACOUSTICS part – 4 Sound Engineering Course
4. Image Enhancement in Frequency Domain
PREDICTION OF ROOM ACOUSTICS PARAMETERS
Volume 62, Issue 1, Pages (April 2009)
INTRODUCTION TO THE SHORT-TIME FOURIER TRANSFORM (STFT)
INTRODUCTION TO ADVANCED DIGITAL SIGNAL PROCESSING
Presentation transcript:

Subjective Assessments of Real-Time Room Dereverberation and Loudspeaker Equalisation Panagiotis Hatziantoniou and John Mourjopoulos AudioGroup, WCL Department of Electrical and Computer Engineering University of Patras, Greece John W. Worley

Slide 2 of 13 Introduction  To perceptual assess room deverberation.  Using, Complex Smoothed room transfer functions (RTF) -v- loudspeaker equalisation.  Measuring multi-dimensional sound quality attributes. F Low-frequency spectral balance. F High-frequency spectral balance. F Phase clarity. F Overall sound quality. F Room size. F Source distance.

Slide 3 of 13 Method: Anechoic inverse filter design  Presentation, free from loudspeaker response coloration.

Slide 4 of 13 Method: Complex Smoothed inverse filter design  Presentation, free from loudspeaker and RTF coloration.

Slide 5 of 13 Inverse filtering using smoothed filters from: “Results for Room Acoustics Equalisation Based on Smoothed Responses” Panagiotis D. Hatziantoniou and John N. Mourjopoulos,114th AES Convention, Amsterdam, March 2003 time domain frequency domain modification compensation

Slide 6 of 13 Test Rooms  L: 7.15m X W: 4.60m X H: 2.90m.  RT = sec (frequency averaged).  L: 10.20m X W: 7.05m: X H:2.65m  RT = 1.1 sec (frequency averaged). Room 1 Laboratory/Listening room Room 2 Classroom

Slide 7 of 13  2I-multi-AFC task.  8 Subjects.  Stimuli  Music  Speech  Castanets  Snare  Exp. Conditions  On-filter -v- Off-filter presentation  Anechoic -v- Smoothed filter  2 loudspeaker pairs  2 rooms Subjective assessment

Slide 8 of 13 Results: Room 1

Slide 9 of 13 Results: Room 2

Slide 10 of 13  Smoothed filter rated higher than anechoic:  High-frequency spectral balance, phase clarity, overall sound quality, & room size.  Listener position = non.sig.  Sig. effect of room:  High-frequency spectral balance, phase clarity, & overall sound quality  Sig. effect of loudspeaker:  Low-frequency spectral balance. Results: MANOVA & ANOVA

Slide 11 of 13 Conclusions  Complex smooth filtering is not listener location specific  A preference for Complex smooth filtering shown in:  Temporal distinctiveness  Mid- to high-frequency spectral balance  Reduces reverberance  Complex smooth filtering has more effect in acoustically poor room than optimum listening room.  Listeners prefer good loudspeakers over poorer loudspeakers in terms of low-frequency spectral balance.  Agreement with objective measures.  Successful measure of multi-dimensional sound quality attributes.

Slide 12 of 13 Future work  Compare filtering methods to commercial dereverberation DSP techniques (ie parametric equalisation).  Measure and test Complex smooth filtering in a multi-purpose hall.  Reduce the subjective measurement variables.  Separately test the temporal and magnitude effect of Complex Smooth dereverberation.

AudioGroup, WCL Department of Electrical and Computer Engineering University of Patras, Greece