Dynamic range compression with low distortion for use in hearing aids and audio systems

Patent metadata

Field	Value
Publication number	US-2016336015-A1
Application number	US-201515113271-A
Country	US
Kind code	A1
Filing date	Jan 27, 2015
Priority date	Jan 27, 2014
Publication date	Nov 17, 2016
Grant date	—

Abstract

Dynamic range compression in the hearing aids is provided for restoring normal loudness of low level sounds without making the high level sounds uncomfortably loud. An apparatus along with a method using sliding-band compression is disclosed for significantly reducing the temporal and spectral distortions generally associated with the currently used single and multiband compression techniques. It; uses a frequency-dependent gain function calculated on the basis of auditory critical bandwidth based short-time power spectrum and the specified hearing thresholds, compression ratios, and attack and release times. It is realized using FFT-based analysis-synthesis and can be integrated with other FFT-based signal processing in hearing aids and audio systems.

First claim

1 - 18 . (canceled)

19 . A method of dynamic range compression with low temporal and spectral distortions for use in hearing aids and audio devices, wherein a digitized input signal is processed by sliding-band compression comprising the steps of:
multiplying samples of said input signal with an analysis window to form overlapping frames; calculating short-time complex spectrum of said input signal by applying discrete Fourier transform (DFT) on said overlapping frames; calculating short-time power spectrum by summing a square of magnitude of samples of said complex spectrum lying in a band centered at each frequency sample; calculating target gain for each frequency sample using said power spectrum and a given frequency-dependent compression function; calculating a gain for each frequency sample of said complex spectrum using said target gain and selected attack and release times; multiplying each frequency sample of said complex spectrum with said gain to obtain an output complex spectrum; calculating an output segment by applying inverse discrete Fourier transform (IDFT) on said output complex spectrum; and resynthesizing an output signal by applying overlap-add on said output segment.

20 . The method as claimed in claim 19 , further comprising: calculating a frequency-dependent compression function from specified hearing thresholds and compression ratios to compensate for frequency-dependent loudness recruitment associated with sensorineural hearing loss.

21 . The method as claimed in claim 19 , wherein the target gain is calculated as a function of frequency using the given frequency-dependent compression function as a linear relationship on logarithmic scale between the short-time power spectrum and the output complex spectrum.

22 . The method as claimed in claim 19 , wherein the target gain is calculated as a function of frequency using a two-dimensional look-up table providing the given frequency-dependent compression function most suited to compensate for an abnormal loudness growth curve of an ear of a hearing-impaired listener.

23 . The method as claimed in claim 19 , wherein the gain is changed smoothly from a previous value towards the calculated target gain in accordance with the selected attack and release times.

24 . The method as claimed in claim 23 , wherein a fast attack is used to avoid an output level from exceeding an upper comfortable listening level during transients, and a slow release is used to avoid a pumping effect or amplification of breathing.

25 . The method as claimed in claim 19 , wherein a bandwidth of the band centered at each frequency sample for calculating the short-time power spectrum is selected to approximate a frequency resolution of an auditory system, wherein the bandwidth changes from a small value at a low frequency end to a large value at a higher frequency end.

26 . The method as claimed in claim 25 , wherein the bandwidth is selected as one-third octave bandwidth, the bandwidth corresponding to equal increments on a mel scale, or auditory critical bandwidth.

27 . The method as claimed in claim 19 , wherein an analysis-synthesis technique based on least-square error minimization is used to avoid perceptible distortions caused by changes in a magnitude response dissociated from a phase response during compression of speech and non-speech audio signals.

28 . The method as claimed in claim 19 , wherein an analysis-synthesis technique based on fast Fourier transform (FFT) is integrated with other FFT-based spectral modifications used in processing of the input signal.

29 . The method as claimed in claim 19 , wherein a feed-forward compression system is used for the sliding-band compression.

30 . An apparatus for dynamic range compression with low temporal and spectral distortions for use in hearing aids and audio devices, the apparatus comprising:
an analog-to-digital converter to convert analog input signal to digital signal; a digital signal processor for sliding-band compression to modify the digital signal from said analog-to-digital converter; and a digital-to-analog converter to convert the modified digital signal from said digital signal processor as an output analog signal; wherein the sliding-band compression comprises the steps of:
multiplying samples of said digital signal with an analysis window to form overlapping frames;
calculating short-time complex spectrum of said digital signal by applying discrete Fourier transform (DFT) on said overlapping frames;
calculating short-time power spectrum by summing a square of magnitude of samples of said complex spectrum lying in a band centered at each frequency sample;
calculating target gain for each frequency sample using said power spectrum and a given frequency-dependent compression function;
calculating a gain for each frequency sample of said complex spectrum using said target gain and selected attack and release times;
multiplying each frequency sample of said complex spectrum with said gain to obtain an output complex spectrum;
calculating an output segment by applying inverse discrete Fourier transform (IDFT) on said output complex spectrum; and
resynthesizing an output signal by applying overlap-add on said output segment.

31 . The apparatus as claimed in claim 30 , wherein the digital signal processor comprises on-chip FFT hardware.

32 . The apparatus as claimed in claim 30 , wherein the analog-to-digital converter and the digital-to-analog converter are configured for input and output, respectively, using DMA (direct memory access) and cyclic buffering for computationally efficient overlap-add operation for analysis-synthesis.

33 . An apparatus for dynamic range compression with low temporal and spectral distortion for use in audio devices, comprising a digital signal processor processing digitized audio signals available in a form of digital samples at regular intervals or in a form of data packets, wherein said digital signal processor performs sliding-band compression comprising the steps of:
multiplying samples of said input signal with an analysis window to form overlapping frames; calculating short-time complex spectrum of said input signal by applying discrete Fourier transform (DFT) on said overlapping frames; calculating short-time power spectrum by summing a square of magnitude of samples of said complex spectrum lying in a band centered at each frequency sample; calculating target gain for each frequency sample using said power spectrum and a given frequency-dependent compression function; calculating a gain for each frequency sample of said complex spectrum using said target gain and selected attack and release times; multiplying each frequency sample of said complex spectrum with said gain to obtain an output complex spectrum; calculating an output segment by applying inverse discrete Fourier transform (IDFT) on said output complex spectrum; and resynthesizing an output signal by applying overlap-add on said output segment.

Assignees

• Indian Inst Technology Bombay
• Inst Of Tech Bombay

Inventors

• Pandey Prem Chand
• Tiwari Nitya

Classifications

• H04R2430/03

  Synergistic effects of band splitting and sub-band processing · CPC title

• G10L19/022 Primary

  Blocking, i.e. grouping of samples in time; Choice of analysis windows; Overlap factoring · CPC title

• H04R25/505

  using digital signal processing · CPC title

• H04R25/353 Primary

  Frequency, e.g. frequency shift or compression · CPC title

• H04R25/356

  Amplitude, e.g. amplitude shift or compression · CPC title