Experimental Performance Analysis of Sound Source Detection with

SRP PHAT-β Anand Ramamurthy,

Harikrishnan Unnikrishnan, Kevin. D. Donohue

UNIVERSITY OF

KENTUCKY College of Engineering

Department of Electrical and Computer EngineeringCenter For Visualization & Virtual Environments

Funded in part by NSF EPSCoR Program

Sound Source Detection

• Objective :– To detect and locate a sound source within a

space of interest.

• Approach– Using spatially distributed microphone array.

• Application– Speech recognition – Teleconferencing

– Security surveillance

Objective

• Detection analysis with experimental data to compare the impact of various implementations of whitening process to enhance sound source detection.

Steered Response Power

• Robust algorithm

• Especially in the presence of multiple interfering sources

• Each point defined by a unique set of delays to the microphone array

z

• Signals received at each microphone aligned together by adding appropriate delay.

• Coherent power is computed

• Power estimate used for detection and localization.

Steered Response Coherent Power

SRCP

∑Compute

Coherent Power

(x,y,z)

1τ

2τ

mτ

1τ 2τ mτUniquely defines (x,y,z)

SRCP …

• Power estimates get corrupted by noises– Interfering sources and ambient noise

(Uncorrelated)

– Reverberations (Highly Correlated)

Coherent Summation

Incoherent Summation

PHAT

• Phase Transform – Spectral whitening

• Lower frequencies have higher contribution to signal power.

• Higher frequencies also contains significant information (phase).

• SRCP- PHAT is a measure of coherence and not the signal magnitude.

PHAT

SRCP – PHAT

• Works well with broad band signals

PHAT - β

• Speech is a combination of narrow and wideband signal.

• β - Controls the extend of whitening

• 0 ≤ β ≤ 1

• This work aims to find the ideal value for β

Experimental Setup

Speakers (sound source)

Off

ice

Wa

ll

Microphones

Field of View

Test Signals Used

• Broad band : 400Hz – 5600 Hz colored noise

• Narrowband : 400Hz – 600 Hz colored noise

• Sampling frequency of 16 kHz

Results

ROC

• Receiver Operation Characteristics

• True Detection vs False Alarm

• Area under the curve gives an Indication of decision making capability

• Used in Biomedical, RADAR applications

Narrow band Broad band

Low

reverb.

High

reverb.

Conclusion

• PHAT – β out performs conventional PHAT in

varied operating conditions

•β ranging from 0.65 – 0.7 would give superior performance for speech signal

•The results are in close agreement with the previous simulation studies.

- Done by Kevin D. Donhue, J. Hannemann and H.G. Dietz

Signal type Low reverb. High Reverb.

Narrow band 0.4 – 0.75 0.2 – 0.7

Broadband 0.65 – 0.9 0.6 – 1