Nitya Tiwari

Speech enhancement using spectral subtraction and cascaded-median based noise estimation for hearing impaired listeners

A spectral subtraction technique is presented for real-time speech enhancement in the aids used by hearing impaired listeners. For reducing computational complexity and memory requirement, it uses a cascaded-median based estimation of the noise spectrum without voice activity detection. The technique is implemented and tested for satisfactory real-time operation, with sampling frequency of 12 kHz, processing using window length of 30 ms with 50% overlap, and noise estimation by 3-frame 4-stage cascaded-median, on a 16-bit fixed-point DSP processor with on-chip FFT hardware. Enhancement of speech with different types of additive stationary and non-stationary noise resulted in SNR advantage of 4 – 13 dB.

Speech enhancement using noise estimation based on dynamic quantile tracking for hearing impaired listeners

Persons with sensorineural hearing loss experience difficulty in speech perception in noisy environments. They can benefit from signal processing for suppressing the background noise in their hearing aids. For such an application, a speech enhancement technique using spectral subtraction and noise spectrum estimation based on dynamic quantile tracking is presented. It does not involve voice activity detection or storage and sorting of past spectral samples. Enhancement of speech corrupted with different types of additive stationary and non-stationary noise showed improvement in speech quality to be equivalent to an SNR advantage of 3 - 6 dB. The technique is implemented and tested for satisfactory real-time operation, with sampling frequency of 10 kHz, on a 16-bit fixed-point DSP processor with on-chip FFT hardware.

A smartphone app-based digital hearing aid with sliding-band dynamic range compression

Listeners with sensorineural hearing loss have degraded speech perception due to frequency-dependent elevation of hearing thresholds, reduced dynamic range, and increased temporal and spectral masking. Signal processing in hearing aids for such listeners uses frequency-selective amplification and dynamic range compression for restoring normal loudness of low-level sounds without making the high-level sounds uncomfortably loud. Sliding-band compression has been reported earlier for reducing the temporal and spectral distortions generally associated with currently used single and multiband compression techniques. The paper presents implementation of sliding-band compression as a smartphone app for use as a hearing aid. The processing involves a frequency-dependent gain function calculated on the basis of 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 such techniques for computational efficiency.

A sliding-band dynamic range compression for use in hearing aids

Sensorineural hearing loss is associated with elevated hearing thresholds, reduced dynamic range, and loudness recruitment. 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. A sliding-band compression is presented 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 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 to save computation. The technique is implemented and tested for satisfactory real-time operation, with sampling frequency of 10 kHz, window length of 25.6 ms with 75% overlap on a 16-bit fixed-point DSP processor with on-chip FFT hardware.

Implementation of a Digital Hearing Aid with User-Settable Frequency Response and Sliding-Band Dynamic Range Compression as a Smartphone App

Persons with sensorineural hearing loss suffer from degraded speech perception caused by frequency-dependent elevation of hearing thresholds, reduced dynamic range and abnormal loudness growth, and increased temporal and spectral masking. For improving speech perception by persons with moderate loss of this type, a digital hearing aid is implemented as an Android-based smartphone app. It uses sliding-band dynamic range compression for restoring normal loudness of low-level sounds without making the high-level sounds uncomfortably loud and for reducing the perceptible temporal and spectral distortions associated with currently used single and multiband compression techniques. The processing involves application of a frequency dependent gain function calculated on the basis of critical bandwidth based short-time power spectrum and is realized using FFT-based analysis-synthesis. The implementation has a touch-controlled graphical user interface enabling the app user to fine tune the frequency-dependent parameters in an interactive and real-time mode.

A JFET-based circuit for realizing a precision and linear floating voltage-controlled resistance

A JFET-based circuit for realizing a precision and linear floating voltage-controlled resistance (VCR) is presented for use in analog multipliers and programmable analog circuits and as a resistance mirror. It uses a matched JFET pair along with an op amp based negative feedback for realizing a precision resistance and a feedback of the source and drain voltages to the gate for realizing a linear floating resistance. The circuit operation is validated through circuit simulation and practical testing.

Speech enhancement and multi-band frequency compression for suppression of noise and intraspeech spectral masking in hearing aids

Sensorineural hearing impairment is associated with increased intraspeech spectral masking and results in degraded speech perception in noisy environment due to increased masking. Speech enhancement using spectral subtraction can be used for suppressing the external noise. Multiband frequency compression of the complex spectral samples has been reported to reduce the effects of increased intraspeech masking. A combination of these techniques is implemented for real-time processing for improving speech perception by persons with moderate sensorineural loss. For reducing computational complexity and memory requirement, spectral subtraction is carried out using a cascaded-median based estimation of the noise spectrum without voice activity detection. Multi-band frequency compression, based on auditory critical bandwidths, is carried out using fixed-frame processing along with least-squares error based signal estimation to reduce the processing delay. To reduce computational complexity the two processing stages share the FFT based analysis-synthesis. The processing is implemented and tested for satisfactory operation, with sampling frequency of 10 kHz, 25.6 ms window with 75% overlap, using a 16-bit fixed-point DSP processor. The real-time operation is achieved with signal delay of approximately 36 ms and using about one-third of the computing capacity of the processor.