A Modified Tunable – Q Wavelet Transform Approach for Tamil Speech Enhancement

Indra, Jamaludin; Shankar, Rahul; Kasthuri, N.; manjuri, S. Geetha

doi:10.1080/03772063.2020.1724836

Cited by 4 publications

(1 citation statement)

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“…For speech processing two band ortho normal wavelet is used which can be associated with ortho normal filter bank [22]. Speech processing of hearing aid can be possible using filter bank which has equal bandwidth and perfect reconstruction features.…”

Section: Two Channel Wavelet Filter Bankmentioning

confidence: 99%

Speech Separation Methodology for Hearing Aid

Esra¹,

Sukhi²

2023

Computer Systems Science and Engineering

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In the design of hearing aids (HA), the real-time speech-enhancement is done. The digital hearing aids should provide high signal-to-noise ratio, gain improvement and should eliminate feedback. In generic hearing aids the performance towards different frequencies varies and non uniform. Existing noise cancellation and speech separation methods drops the voice magnitude under the noise environment. The performance of the HA for frequency response is non uniform. Existing noise suppression methods reduce the required signal strength also. So, the performance of uniform sub band analysis is poor when hearing aid is concern. In this paper, a speech separation method using Non-negative Matrix Factorization (NMF) algorithm is proposed for wavelet decomposition. The Proposed non-uniform filter-bank was validated by parameters like band power, Signal-to-noise ratio (SNR), Mean Square Error (MSE), Signal to Noise and Distortion Ratio (SINAD), Spurious-free dynamic range (SFDR), error and time. The speech recordings before and after separation was evaluated for quality using objective speech quality measures International Telecommunication Union -Telecommunication standard ITU-T P.862.

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Section: Two Channel Wavelet Filter Bankmentioning

confidence: 99%