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Author: search.filters.author.Poluboina, V.Subject: search.filters.subject.Speech recognition

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    Contribution of frequency compressed temporal fine structure cues to the speech recognition in noise: An implication in cochlear implant signal processing
    (Elsevier Ltd, 2022) Poluboina, V.; Pulikala, A.; Pitchai Muthu, A.N.
    The study investigated the effect of proportionally frequency compressed encoding of temporal fine structure information on speech perception in noise using vocoder simulations of cochlear implant signal processing. The study proposed a pitch synchronous overlap-add algorithm (PSOLA) for downward frequency shifting of TFS. The speech recognition scores (SRS) were measured at −10 dB, 0 dB, and +10 dB for eight signal processing conditions corresponding to sinewave vocoder without TFS (NO-TFS), four unshifted TFS conditions including full band TFS, TFS up to 2000, 1000, and 600 Hz, and three conditions with PSOLA which shifted 2000, 1000 and 600 Hz TFS to 1000, 500 and 300 Hz respectively. The original envelope was unchanged across the conditions. SRS at +10 dB and −10 dB SNR reached ceiling and floor respectively, in most conditions. Hence, SRS at 0 dB SNR was compared across the conditions. The results showed that the SRS was highest with full band TFS and lowest for the NO-TFS condition.The SRS for TFS 600 Hz shifted to 300 Hz through PSOLA was higher than the NO-TFS condition. Study findings suggest that encoding TFS by proportional frequency compression results in better speech perception in noise compared to NO-TFS. An important observation of this current study is that the speech recognition was better than the sine wave vocoder for all TFS conditions including frequency compressed 600 Hz TFS. © 2021 Elsevier Ltd
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    An Improved Noise Reduction Technique for Enhancing the Intelligibility of Sinewave Vocoded Speech: Implication in Cochlear Implants
    (Institute of Electrical and Electronics Engineers Inc., 2023) Poluboina, V.; Pulikala, A.; Pitchaimuthu, A.N.P.
    A cochlear implant (CI) is the most suitable option for individuals with severe profound hearing loss. CI restores the audibility to near perfection and offers good speech understanding in quiet. However, the speech perception in noise with CIs is less optimal as most speech coding strategies of CIs encode only the temporal envelope. Besides the current CI signal coding strategies lacks sophisticated pre-processing. In the current study, we proposed a novel pre-processing method to improve speech Intelligibility in noise and tested using the acoustic simulations of cochlear implants. The proposed noise reduction technique aims to minimize the mean square error (MSE) between the temporal envelopes of the enhanced speech and its clean speech. Therefore, the proposed method will be suitable for CI applications. This paper provides an analysis of the theoretical derivation of the noise suppression function and also the performance evaluation using objective and subjective tests. The effectiveness of the proposed method was objectively evaluated using the SRMR-CI and ESTOI. Additionally, speech recognition through the acoustic simulations of the cochlear implant was done for the subjective evaluation. Performance of the proposed method was compared with the Weiner filter (WF) and sigmoidal functions. The sinewave vocoder was used to simulate the cochlear implant perception. Both objective and subjective scores revealed that the performance of the proposed technique is superior to the WF and sigmoidal function. © 2013 IEEE.