2008 Tohoku-Section Joint Convention of Institutes of Electrical and Information Engineering, Japan

Blind Multichannel Identificationin Acoustic Space
using Numerous Channels^Takuma Okamoto, Yukio Iwaya and Yoiti
SuzukiResearch Institute of Electrical Communication
Graduate School of Information Science
Tohoku University, Japan1

Outline
1. Introduction
2. Blind Multichannel Identification
3. Computer Simulation
4. Conclusion
2

Introduction
Reconstruction techniques of Sound field information as cinemas
and home theater
For high realistic sensation
The sound produced by these systems is, however, unrealistic!!

Developing the system of recording, recognition and reproduction
the sound field information in the real environment accurately
Sound information
Sound field information

Sound source waveform data

Field information
Reflected sound information
Sound source positions
Sound source number3

Surrounding microphone array
Recording sound field information in the real environment
Spec of this room
・5.18 × 3.38 × 2.22 (m)・walls20×2，36×2
・ceiling
45
sum total
157 chSurrounding microphone array @ RIEC

・Installed 30 cm from all walls
・Separated from each other by 50 cm
・48 kHz sampling(Synchronized 157 ch)

Estimating and extract sound field information using only 4
the input signals of 157 microphones

Accurately extraction ofsound field information
Extraction of sound field information =Estimation of the room transfer functions (=impulse responses)
・Inverse filtering by MINT (M. Miyoshi et al 1989)→ extraction of source waves
・Compute sound arrival time
→ extraction of source positions
・Source signal – input signals→ extraction of reflected soundMultiple Input Multiple Output model(MIMO model)

5

Blind multichannel identification
using 157 input signals
Estimation of the impulse responses from only input channels
Blind multichannel Identification (BMI) Y. Sato 1975
FNMLMS(Frequency-domain normalized multichannel LMS)
Y. Huang et al 2003
applied to BMI for estimating impulse responses inSIMO model

Y. Huang et al have used only three input
signals (= much fewer than for our system)
Single Input Multiple Output model(SIMO model)

aInvestigationof the performance
aof FNMLMS using 157 input signals 6

Blind multichannel identification basedon second order statistics
The output signal of i-th channel xi(n)(1)

In vector form

Single Input Multiple Output model(SIMO model)

7

Time-domain multichannel LMS
From eq. (1)(2)

Therefore,and,※8Time-domain multichannel LMS (2)Estimated impulse responses

An error signal(3)
The cost function(4)
Constraint
Multichannel LMS
9Frequency-domain multichannel LMS
By taking advantage of the computational efficiency of the FFT
a convolution of two signals can be quickly calculated
Discrete Fourier transform processes a time sequence like a filterbank, which orthogonalizes the data,
the coefficients of a frequency-domain adaptive filter can converge
independently or even uniformly if the update is normalized properly
Frequency-domain multichannel LMS (FMLMS)
Calculating a convolution by FFT and the cost function is frequency-domain

Frequency-domain normalized multichannel LMS (FNMLMS)
Introducing the forgetting factor to FMLMS and accelerate
the convergence10Computer simulation
Simulation conditions
sound sourse s(n): Gaussian white noise
impulse response hi: 64 taps of FIR filter (made by image method)numbers of channels M : 3 and 157
step size parameter ρf : 1.0
Image method J. B. Allen et al 1979

Direct soundFirst reflected soundSecond reflected soundReal and image source positions
11

Simulation results

Generated Impulse Response (channel 1)

Estimated Impulse Response (N = 3)
12

Simulation results (2)Generated Impulse Response (channel 1)

Estimated Impulse Response (N = 3)
13

Simulation results (3)The cost function

Generated Impulse Response (channel 1)(4)

Estimated Impulse Response (N = 3)
14

Conclusion
Comparing the performance of FNMLMS using 3 and 157 channels
Using 3 channels
Local solution is computed for few channels
Using 157 channels
True solution is computed

FNMLMS using 157 channels is superior to that using 3 channels !!
15