A Novel Approach of Speech Recognition Using System Identification
With the growing of artificial intelligence and the usage of sound commands the needs for a high accuracy speech recognition increases. Many researches are done in this area using different kinds of methods and approaches. In this research two algorithms have been introduced. The autoregressive sys...
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| Format: | Article |
| Language: | English |
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University of Diyala
2019-09-01
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| Series: | Diyala Journal of Engineering Sciences |
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| Online Access: | https://djes.info/index.php/djes/article/view/68 |
| _version_ | 1811282738778472448 |
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| author | Ibrahim Sadoon Fatah |
| author_facet | Ibrahim Sadoon Fatah |
| author_sort | Ibrahim Sadoon Fatah |
| collection | DOAJ |
| description |
With the growing of artificial intelligence and the usage of sound commands the needs for a high accuracy speech recognition increases. Many researches are done in this area using different kinds of methods and approaches. In this research two algorithms have been introduced. The autoregressive system identification and the FIR Wiener filter. The objective of this research is to show the robustness of system identification in terms of speech recognition.Both algorithms have been implemented and tested using MATLAB where the process is done by recording full sentences from different subjects under two conditions which are clear and noisy background. For each sentence, it has been recorded two timesfor each subject; the first one was used for testing and the second sentence was used for validation. The results show that both algorithms are giving an accurate prediction when the used data are from the same subject with clear background. The advantage of system identification over the Weiner filter is shine when using noisy signals. Another advantage of using system identification for speech recognition is it can distinguish the sound difference when same sentence from different subjects is used where the Weiner filter in some cases passes them as from the same subject. This could be a huge issue if the algorithm is used for security reasons
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| first_indexed | 2024-04-13T01:57:58Z |
| format | Article |
| id | doaj.art-30100ff298b54976b758184bd0370ac9 |
| institution | Directory Open Access Journal |
| issn | 1999-8716 2616-6909 |
| language | English |
| last_indexed | 2024-04-13T01:57:58Z |
| publishDate | 2019-09-01 |
| publisher | University of Diyala |
| record_format | Article |
| series | Diyala Journal of Engineering Sciences |
| spelling | doaj.art-30100ff298b54976b758184bd0370ac92022-12-22T03:07:43ZengUniversity of DiyalaDiyala Journal of Engineering Sciences1999-87162616-69092019-09-0112310.24237/djes.2019.12309A Novel Approach of Speech Recognition Using System IdentificationIbrahim Sadoon Fatah0Electronic Dep. – Engineering Collage – Daiyla Universit With the growing of artificial intelligence and the usage of sound commands the needs for a high accuracy speech recognition increases. Many researches are done in this area using different kinds of methods and approaches. In this research two algorithms have been introduced. The autoregressive system identification and the FIR Wiener filter. The objective of this research is to show the robustness of system identification in terms of speech recognition.Both algorithms have been implemented and tested using MATLAB where the process is done by recording full sentences from different subjects under two conditions which are clear and noisy background. For each sentence, it has been recorded two timesfor each subject; the first one was used for testing and the second sentence was used for validation. The results show that both algorithms are giving an accurate prediction when the used data are from the same subject with clear background. The advantage of system identification over the Weiner filter is shine when using noisy signals. Another advantage of using system identification for speech recognition is it can distinguish the sound difference when same sentence from different subjects is used where the Weiner filter in some cases passes them as from the same subject. This could be a huge issue if the algorithm is used for security reasons https://djes.info/index.php/djes/article/view/68System identificationARXFIR filterWiener filterspeech recognitionsignal processing |
| spellingShingle | Ibrahim Sadoon Fatah A Novel Approach of Speech Recognition Using System Identification Diyala Journal of Engineering Sciences System identification ARX FIR filter Wiener filter speech recognition signal processing |
| title | A Novel Approach of Speech Recognition Using System Identification |
| title_full | A Novel Approach of Speech Recognition Using System Identification |
| title_fullStr | A Novel Approach of Speech Recognition Using System Identification |
| title_full_unstemmed | A Novel Approach of Speech Recognition Using System Identification |
| title_short | A Novel Approach of Speech Recognition Using System Identification |
| title_sort | novel approach of speech recognition using system identification |
| topic | System identification ARX FIR filter Wiener filter speech recognition signal processing |
| url | https://djes.info/index.php/djes/article/view/68 |
| work_keys_str_mv | AT ibrahimsadoonfatah anovelapproachofspeechrecognitionusingsystemidentification AT ibrahimsadoonfatah novelapproachofspeechrecognitionusingsystemidentification |