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Wyświetlanie 1-3 z 3
Tytuł:
Towards spike-based speech processing: a biologically plausible approach to simple acoustic classification
Autorzy:
Uysal, I.
Sathyendra, H.
Harris, J. G.
Powiązania:
https://bibliotekanauki.pl/articles/907947.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
kodowanie synchroniczne
blokowanie fazowe
percepcja mowy
psychoakustyka
rozpoznawanie mowy
spike coding
synchrony coding
phase locking
speech perception
psychoacoustics
speech recognition
Opis:
Shortcomings of automatic speech recognition (ASR) applications are becoming more evident as they are more widely used in real life. The inherent non-stationarity associated with the timing of speech signals as well as the dynamical changes in the environment make the ensuing analysis and recognition extremely difficult. Researchers often turn to biology seeking clues to make better engineered systems, and ASR is no exception with the usage of feature sets such as Mel frequency cepstral coefficients, which employ filter banks similar to cochlear filter banks in frequency distribution and bandwidth. In this paper, we delve deeper into the mechanics of the human auditory system to take this biological inspiration to the next level. The main goal of this research is to investigate the computation potential of spike trains produced at the early stages of the auditory system for a simple acoustic classification task. First, various spike coding schemes from temporal to rate coding are explored, together with various spike-based encoders with various simplicity levels such as rank order coding and liquid state machine. Based on these findings, a biologically plausible system architecture is proposed for the recognition of phonetically simple acoustic signals which makes exclusive use of spikes for computation. The performance tests show superior performance on a noisy vowel data set when compared with a conventional ASR system.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2008, 18, 2; 129-137
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Coding effects on changes in formant frequencies in Japanese speech signals
Autorzy:
Kucharski, Mateusz
Brachmański, Stefan
Powiązania:
https://bibliotekanauki.pl/articles/128083.pdf
Data publikacji:
2019
Wydawca:
Politechnika Poznańska. Instytut Mechaniki Stosowanej
Tematy:
speech
speech coding
formants
mowa
kodowanie mowy
formanty
Opis:
This paper presents results of research on effects of lossy coding on formant frequencies for japanese speech signals. Additionally changes in pitch of the voice were inspected. For this research four most popular lossy coding standards were chosen, MP3, WMA, AAC and OGG, and compared to original WAVE files. Audio files were created by the author based on ITU-T P.501 recommendation in two sampling frequencies, 16 kHz and 48 kHz, and converted into chosen codecs. To extract the data from audio files, open license software Praat was used. Due to discovered differences in time duration between original and encoded files, that also differed between individual codecs, only OGG and WMA standards were compared directly. MP3 and AAC standards were divided into Japanese syllables, averaged and then compared into also averaged WAVE files. Results were additionally compared to FLAC lossless codec.
Źródło:
Vibrations in Physical Systems; 2019, 30, 1; 1-8
0860-6897
Pojawia się w:
Vibrations in Physical Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Lossy coding impact on speech recognition with convolutional neural networks
Autorzy:
Kucharski, Mateusz
Powiązania:
https://bibliotekanauki.pl/articles/24201985.pdf
Data publikacji:
2022
Wydawca:
Politechnika Poznańska. Instytut Mechaniki Stosowanej
Tematy:
lossy coding
convolutional neural networks
speech recognition
kodowanie stratne
konwolucyjne sieci neuronowe
rozpoznawanie mowy
Opis:
This paper presents research of lossy coding impact on speech recognition with convolutional neural networks. For this purpose, google speech commands dataset containing utterances of 30 words was encoded using four most common all-purpose codecs: mp3, aac, wma and ogg. A convolutional neural network was taught using part of the original files and later tested with the rest of the files, as well as their counterparts encoded with different codecs and bitrates. The same network model was also taught using mp3 encoded data showing the biggest loss in effectiveness of the previous network. Results show that lossy coding does have an effect on speech recognition, especially for low bitrates.
Źródło:
Vibrations in Physical Systems; 2022, 33, 3; art. no. 2022302
0860-6897
Pojawia się w:
Vibrations in Physical Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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