8/15/2015 1 P. C. Pandey, "Signal processing for hearing aids: Challenges and some solutions,” Invited talk, Workshop “Radar and Sonar Signal Processing,” NSTL Visakhapatnam, 17-21 Aug 2015 Workshop Coordinator: Ms. M. Vijaya < vijaya.m @ nstl.drdo.in > Session: 21 Aug 2015, 1100 to 1230 =========================================================================== Part B Sliding-band Dynamic Range Compression (Ref: N. Tiwari & P. C. Pandey, NCC 2014, Paper No.1569847357) 2/25 Overview 1. Introduction 2. Sliding-band Dynamic Range Compression 3. Offline & Real-time Implementations 4. Test Results 5. Summary & Conclusion
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8/15/2015
1
P. C. Pandey, "Signal processing for hearing aids: Challenges and some
solutions,” Invited talk, Workshop “Radar and Sonar Signal Processing,”
NSTL Visakhapatnam, 17-21 Aug 2015
Workshop Coordinator: Ms. M. Vijaya < vijaya.m @ nstl.drdo.in >
Session: 21 Aug 2015, 1100 to 1230===========================================================================
Part B
Sliding-band Dynamic
Range Compression
(Ref: N. Tiwari & P. C. Pandey, NCC 2014, Paper No.1569847357)
2/25
Overview
1. Introduction
2. Sliding-band Dynamic Range Compression
3. Offline & Real-time Implementations
4. Test Results
5. Summary & Conclusion
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1. Introduction
Dynamic range compressionTo present sounds comfortably within the limited dynamic range of the
listener by amplifying the low level sounds without making the high level
sounds uncomfortably loud.
Processing steps• Input level estimation
• Gain calculation based on input level
• Multiplication of input with gain function
• Output resynthesis
Classification of compression schemes• On the basis of signal level calculation: single-band or multiband
• On the basis of gain control method: feedback or feed-forward
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Processing
Gain dependent on the
dynamically varying signal level.
Parameters:
• Compression threshold (TH)
• Compression ratio (CR)
• Attack & release time
Problems
Single-band dynamic range compression
• Compensation for frequency-dependent loudness growth not feasible.
• Power mostly contributed by low-frequency components
→ level of of high-frequency components controlled by low-frequency
components
→ Inaudibility of high frequency components, distortions in temporal
envelope
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Multiband dynamic range compression
General scheme of processing
Spectral components of the input signal divided in multiple bands and the
gain for each band calculated on the basis of signal power in that band.
Parameters (band specific): compression threshold TH, compression ratio
CR, attack & release time for detection.
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Lippmann et al. (1980): 16-channel compression
9% improvement in recognition score over linear amplification.
Asano et al.(1991): Multiband dynamic range compression realized as a single
time-varying FIR filter & implemented on a 32-bit DSP fixed-point processor
Less spectral distortion due to smoothened frequency response of FIR filter.
Stone et al. (1999): Comparison of single and four-channel compression
schemes & effect of varying CR, TH, and attack & release times
Intelligibility & quality tests showed no specific preference for schemes.
Li et al. (2000): Wavelet-based compression (7 octave sub-band analysis using
wavelet filter bank & resynthesis after applying a logarithmic compression on
the wavelet coefficients)
Increase in intelligibility without introducing noticeable distortions.
Magotra et al. (2000): Multiband dynamic range compression using a 16-bit
fixed-point processor
Taylor's series approximation used for the compression function to reduce
computations in gain calculation.
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Disadvantages of multiband compression
• Spurious spectral distortions
• Reduction in spectral contrasts and modulation depth
• Distortion in spectral shape of formants lying across the
band boundaries
• Distortion of formant transitions across the adjacent bands
• Time-varying magnitude response without corresponding
variation in the phase response leading to quality