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![Page 1: 1 Reconfigurable Acceleration of Microphone Array Algorithms for Speech Enhancement Ka Fai Cedric Yiu, Yao Lu, Xiaoxiang Shi The Hong Kong Polytechnic.](https://reader035.fdocuments.in/reader035/viewer/2022070401/56649f1a5503460f94c2fa22/html5/thumbnails/1.jpg)
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Reconfigurable Acceleration of Microphone ArrayAlgorithms for Speech Enhancement
Ka Fai Cedric Yiu, Yao Lu, Xiaoxiang ShiThe Hong Kong Polytechnic University
Chun Hok Ho, Wayne LukImperial College London
Nedelko GrbricBlekinge Institute of Technology
3 Jul 2008ASAP 2008
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Contributions
1. FPGA-based hardware architecture for acoustic beamformer
calibrated signals subband processing
2. Bitwidth analysis to explore suitable bitwidth of the system
3. FPGA at 175MHz: 42 times faster than software at 3.2GHz
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Handsfree operation in a noisyenvironment
Speech echoes will appear Disturbing noise, such as:
Engine and fan noise Wind and tire friction
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Speech extraction with microphone arrays (beamforming)
Microphone arrays allows us to use spatial selectivity (directional hearing)
Microphones separated in space can suppress unwanted locations while passing signals from wanted locations
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Narrowband beamforming principle
Spatial aliasing occurs if the distance
between microphones exceeds half
signal wavelength
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Drawbacks with narrowband beamformers
Disturbing noise directions are not especially taken into consideration
Microphone placement must be accurate (or carefully calibrated)
Temporal information is not taken into consideration
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Broadband beamformer structure
FIR-filter
FIR-filter
FIR-filter
FIR-filter
FIR-filter
FIR-filter
Angle of hearing
Angle of hearing
Microphones
Output
By choosing appropriate FIR filters the angle of hearing can be adjusted for
each frequency
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Adaptive beamforming
In order to track variations in the noise situation and to avoid expensive calibration procedures an adaptive scheme is used
It consists of two phases Calibration mode Operation mode
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Phase 1: Calibration mode – Select desired location
Speaker says a short sentence in a silent car
Microphones
Estimate covariance matrices
Determine coefficients for each filter
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Phase 2: Operation mode – Speech extraction while driving
Microphones
Adapting
Beamformer
Output
Speech
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1. FPGA-based beamformer
Low non-recurring engineering cost Architecture exploration Relatively easy to adapt new algorithms Adjust filter length in different environment Embedded processor to produce a system-
on-a-chip (SoC) solution software speech recogniser
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Comparison between subband and time-domain implementations
2)]2([time ILILP
22 )]ML(I
MLM[IfreqP
(#channels I= 6)
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Subband beamformer structure
Angle of hearing
Angle of hearing Mul
ticha
nnel
Subb
and
tran
sfor
mat
ion
Each branch
#I Subband signals
#K Beamformers
Sing
le-c
hann
elSu
bban
dR
econ
stru
ctio
n
#I M icrophones
O utp ut
x1(n )
x2(n )
x3(n )
x4(n )
x I (n )
y(n )
w
w
w
w
w ( K - 1 )
(3 )
( 2 )
(1)
( 0 )
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FPGA-based architecture
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DMA interface
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2. Bitwidth optimisation
Software implementation is based on MATLAB
Floating point implementation is expensive on FPGA
Fixed point implementation Integer width: avoid overflow Saturation arithmetic: overflow protection Fraction width: sufficient accuracy relative to
floating point
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Optimisation results
Input signal Noise signal
Double precision floating point output Optimised fixed point output
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3. Implementation results
Target FPGA: Xilinx Virtex 4 SX55 Slice used: 5937 (12%) DSP48 used: 72 (14%) Block RAM used: 8 (2%) Operating frequency: 175MHz Processing rate: 43k sample per second Pentium 4 3.2GHz processing rate: 7.2k sps 6 times faster for 1 instance
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Multiple instances
Scalable by embedding more beamformer instances Useful in the case where more than one signal
sources in a system 7 instances can achieve 42 times speed up while
running at 175MHz
Instances Frequency (MHz) Slices DSP48 Speed up
1 175 12% 14% 6.0
3 175 36% 42% 17.9
5 175 60% 70% 29.8
7 175 84% 98% 41.7
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Future work
Implement partial reconfiguration on the filter length based on the change of the environment.
Embed a speech recogniser as a performance indicator to adjust the filter length.
Optimise the power consumption by reducing the number of glitches in the system.
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Conclusion
Two different beamforming algorithms have represented Narrowband and broadband
Subband processing FPGA architecture
Processing element DMA interface
Bitwidth optimisation 7 instances of beamformer is 42 time faster