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Wyszukujesz frazę "isolated speech recognition" wg kryterium: Temat


Wyświetlanie 1-3 z 3
Tytuł:
Estimation of Hardware Requirements for Isolated Speech Recognition on an Embedded Systems
Autorzy:
Kłobucki, K.
Mąka, T.
Tematy:
isolated speech recognition
ASR
resources estimation
Pokaż więcej
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:
https://bibliotekanauki.pl/articles/227186.pdf  Link otwiera się w nowym oknie
Opis:
In recent years, speech recognition functionality is increasingly being added in embedded devices. Because of limited resources in these devices, there is a need to assess whether the defined speech recognition system is feasible within given constraints, as well as estimating how many resources the system needs. In this paper, an attempt has been taken to define a technique for estimating hardware resources usage in the speech recognition task. To determine the parameters and their dependencies in this task, the two systems were tested. The first system utilized Dynamic Time Warping pattern matching technique, the second used Hidden Markov Models. For each case, the measurement of recognition rate and time, vocabulary database size and learning time has been performed. Obtained results have been exploited to define linear and polynomial regression models, and finally, an estimation algorithm has been developed using these models. After testing proposed approach, it was observed that even low-end mobile phones have sufficient hardware resources for realisation of isolated speech recognition system.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Effect of Time-domain Windowing on Isolated Speech Recognition System Performance
Autorzy:
Ananthakrishna, Thalengala
Anitha, H.
Girisha, T.
Tematy:
hidden Markov model
HMM
isolated speech recognition system
ISR
Kannada language
mono-phone model
Mel frequency cepstral coefficients
MFCC
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Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:
https://bibliotekanauki.pl/articles/2055228.pdf  Link otwiera się w nowym oknie
Opis:
Speech recognition system extract the textual data from the speech signal. The research in speech recognition domain is challenging due to the large variabilities involved with the speech signal. Variety of signal processing and machine learning techniques have been explored to achieve better recognition accuracy. Speech is highly non-stationary in nature and therefore analysis is carried out by considering short time-domain window or frame. In the speech recognition task, cepstral (Mel frequency cepstral coefficients (MFCC)) features are commonly used and are extracted for short time-frame. The effectiveness of features depend upon duration of the time-window chosen. The present study is aimed at investigation of optimal time-window duration for extraction of cepstral features in the context of speech recognition task. A speaker independent speech recognition system for the Kannada language has been considered for the analysis. In the current work, speech utterances of Kannada news corpus recorded from different speakers have been used to create speech database. The hidden Markov tool kit (HTK) has been used to implement the speech recognition system. The MFCC along with their first and second derivative coefficients are considered as feature vectors. Pronunciation dictionary required for the study has been built manually for mono-phone system. Experiments have been carried out and results have been analyzed for different time-window lengths. The overlapping Hamming window has been considered in this study. The best average word recognition accuracy of 61.58% has been obtained for a window length of 110 msec duration. This recognition accuracy is comparable with the similar work found in literature. The experiments have shown that best word recognition performance can be achieved by tuning the window length to its optimum value.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Visualization of stages of determining cepstral factors in speech recognition systems
Autorzy:
Proksa, R.
Tematy:
rozpoznawanie mowy
LPCC
MFCC
wyizolowane słowo
sygnały mowy
speech recognition
cepstral coefficients
isolated word
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Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Powiązania:
https://bibliotekanauki.pl/articles/333103.pdf  Link otwiera się w nowym oknie
Opis:
The article presents two methods of determination of cepstral parameters commonly applied in digital signal processing, in particular in speech recognition systems. The solutions presented are part of a project aimed at developing applications allowing to control the Windows operating system with voice and the use of MSAA (Microsoft Active Accessibility). The analysed voice signal has been visually presented at each of the crucial stages of developing cepstral coefficients.
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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