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Indicon2013, Mumbai, 13-15 Dec. 2013, Paper No. 524 (Track 4.1, Sat., 14th Dec., 1730 1900)

Speech Enhancement and Multi-band Frequency Compression for Suppression of Noise and Intraspeech Spectral Masking in Hearing Aids

Nitya Tiwari, Santosh K. Waddi, Prem C. Pandey

{nitya, pcpandey} @ ee.iitb.ac.insantosh4b6 @ gmail.com

IIT Bombaynitya@ee.iitb.ac.in, pcpandey@ee.iitb.ac.in, santosh4b6@gmail.com EE Dept., IIT BombayOverviewIntroductionNoise SuppressionMulti-band Frequency CompressionImplementation for Real-time ProcessingTest ResultsSummary & ConclusionEE Dept., IIT Bombay#/24nitya@ee.iitb.ac.in, pcpandey@ee.iitb.ac.in, santosh4b6@gmail.com 1. IntroductionSensorineural hearing lossIncreased hearing thresholds and high frequency lossDecreased dynamic range & abnormal loudness growthIncreased spectral & temporal masking Degraded speech perception, particularly in noisy environment

Signal processing in hearing aidsFrequency selective amplificationAutomatic volume controlMultichannel dynamic range compression (settable attack time, release time, and compression ratios) EE Dept., IIT Bombay#/24nitya@ee.iitb.ac.in, pcpandey@ee.iitb.ac.in, santosh4b6@gmail.com Single-input speech enhancement for reducing the background noise (Boll 1979, Berouti et al.1979, Martin 1994, Loizou 2007, Paliwal et al. 2010)Dynamic estimation of non-stationary noise spectrumduring non-speech segments using voice activity detection, orcontinuously using statistical techniquesEstimation of noise-free speech spectrum spectral noise subtraction, ormultiplication by noise suppression functionSpeech resynthesis using enhanced magnitude and noisy phaseEE Dept., IIT Bombay#/24nitya@ee.iitb.ac.in, pcpandey@ee.iitb.ac.in, santosh4b6@gmail.com Multi-band frequency compression for reducing the effect of increased spectral masking (Arai et al. 2004, Kulkarni et al. 2012)Splitting short-time spectrum into analysis bands and compressing the spectral samples towards the band center, for presenting the speech energy in relatively narrow bands to avoid masking by adjacent spectral components. Segmentation and spectral analysis Analysis-synthesis: fixed-frame or pitch-synchronousAnalysis bands: constant bandwidth or auditory critical bandwidthSpectral modification Modifying magnitude spectrum with original phase (Arai et al. 2004)Modifying complex spectrum to reduce computation & processing related artifacts (Kulkarni et al. 2012)Speech resynthesis using overlap add methodEE Dept., IIT Bombay#/24nitya@ee.iitb.ac.in, pcpandey@ee.iitb.ac.in, santosh4b6@gmail.com Research objective Real-time single-input speech enhancement and multi-band frequency compression for improving speech perception by persons with moderate sensorineural loss.

Main challenges Noise estimation without voice activity detection Multi-band frequency compression with low processing artifactsLow signal delay (algorithmic + computational) for real-time applicationLow computational complexity & memory requirement for implementation on a low-power processor EE Dept., IIT Bombay#/24nitya@ee.iitb.ac.in, pcpandey@ee.iitb.ac.in, santosh4b6@gmail.com Proposed techniqueSpectral subtraction using cascaded-median based continuous updating of the noise spectrum, without using voice activity detectionMulti-band frequency compression based on least square error estimation (LSEE) of modified spectrumInvestigations using offline implementationSelection of processing parametersReal-time implementation 16-bit fixed-point DSP with on-chip FFT hardwareEvaluation of the implementationsInformal listening, PESQ measure EE Dept., IIT Bombay#/24nitya@ee.iitb.ac.in, pcpandey@ee.iitb.ac.in, santosh4b6@gmail.com 2. Noise SuppressionPower subtractionWindowed speech spectrum = Xn(k)Estimated noise mag. spectrum = Dn(k)Estimated speech spectrum Yn(k) = [|Xn(k)|2 (Dn(k))2 ] 0.5 e j