Whispered speech recognition based on gammatone filterbank cepstral coefficients

Markovic, Branko; Galic, Jovan; Grozdic, Dorde T.; Jovičić, Slobodan; Mijic, Miomir

doi:10.1134/s1064226917110134

Cited by 4 publications

(2 citation statements)

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“…Besides, three experiments were conducted to test and record the results of three existing noise reduction techniques to be compared with the first experiment. They are Spectral Subtraction [22], Wiener filter [23], and Gammatone filter [24]. All these techniques have been implemented in MATLAB software.…”

Section: Resultsmentioning

confidence: 99%

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An ensemble technique for speech recognition in noisy environments

Habeeb

Fadhil

Jurn

et al. 2020

IJEECS

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<span>Automatic speech recognition (ASR) is a technology that allows a computer and mobile device to recognize and translate spoken language into text. ASR systems often produce poor accuracy for the noisy speech signal. Therefore, this research proposed an ensemble technique that does not rely on a single filter for perfect noise reduction but incorporates information from multiple noise reduction filters to improve the final ASR accuracy. The main factor of this technique is the generation of K-copies of the speech signal using three noise reduction filters. The speech features of these copies differ slightly in order to extract different texts from them when processed by the ASR system. Thus, the best among these texts can be elected as final ASR output. The ensemble technique was compared with three related current noise reduction techniques in terms of CER and WER. The test results were encouraging and showed a relatively decreased by 16.61% and 11.54% on CER and WER compared with the best current technique. ASR field will benefit from the contribution of this research to increase the recognition accuracy of a human speech in the presence of background noise.</span>

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Section: Resultsmentioning

confidence: 99%

“…(Filter 3) The Gammatone filter was designed to express the performance of the human auditory system and to improve the automatic speech recognition system [14,24]. It is a linear filter that uses logarithmically spaced defined in the impulse response time, which is measured by the product of a sinusoidal tone and gamma distribution.…”

Section: Proposed Techniquementioning

confidence: 99%