Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman
The automatic speech recognition (ASR) field has become one of the leading speech technology areas using artificial intelligence (AI) approaches. Despite all of the advances in the speech recognition area, the problem is far from being completely solved. Various methods have been introduced to devel...
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| Format: | Book Section |
| Language: | en |
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Institute of Graduate Studies, UiTM
2012
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| Online Access: | https://ir.uitm.edu.my/id/eprint/19099/1/ABS_NORAINI%20SEMAN%20TDRA%20VOL%201%20IGS%2012.pdf https://ir.uitm.edu.my/id/eprint/19099/ |
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| _version_ | 1833060487723483136 |
|---|---|
| author | Seman, Noraini |
| author_facet | Seman, Noraini |
| author_sort | Seman, Noraini |
| building | Tun Abdul Razak Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Mara |
| content_source | UiTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | The automatic speech recognition (ASR) field has become one of the leading speech technology areas using artificial intelligence (AI) approaches. Despite all of the advances in the speech recognition area, the problem is far from being completely solved. Various methods have been introduced to develop an efficient ASR system. A variety of automatic knowledge acquisition or learning and adaptation concepts need to be established in speech recognition using AI approaches. These key concepts can only be implemented using artificial neural networks (ANNs) approach. However, traditional ANNs have many fundamental problems regarding a long and uncertain training process, which in most cases learning or training of a neural network is based on a trial and error method. Genetic Algorithm (GA) based learning technique provides an alternative way that involves controlling the learning complexity by adjusting the number of weights of the ANN. However, due to the stochastic nature of this algorithm, the learning process can reach an optimal solution with much higher probability than many standard neural network techniques. |
| format | Book Section |
| id | my.uitm.ir-19099 |
| institution | Universiti Teknologi Mara |
| language | en |
| publishDate | 2012 |
| publisher | Institute of Graduate Studies, UiTM |
| record_format | eprints |
| spelling | my.uitm.ir-190992018-06-11T00:54:33Z https://ir.uitm.edu.my/id/eprint/19099/ Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman Seman, Noraini Malaysia The automatic speech recognition (ASR) field has become one of the leading speech technology areas using artificial intelligence (AI) approaches. Despite all of the advances in the speech recognition area, the problem is far from being completely solved. Various methods have been introduced to develop an efficient ASR system. A variety of automatic knowledge acquisition or learning and adaptation concepts need to be established in speech recognition using AI approaches. These key concepts can only be implemented using artificial neural networks (ANNs) approach. However, traditional ANNs have many fundamental problems regarding a long and uncertain training process, which in most cases learning or training of a neural network is based on a trial and error method. Genetic Algorithm (GA) based learning technique provides an alternative way that involves controlling the learning complexity by adjusting the number of weights of the ANN. However, due to the stochastic nature of this algorithm, the learning process can reach an optimal solution with much higher probability than many standard neural network techniques. Institute of Graduate Studies, UiTM 2012 Book Section PeerReviewed text en https://ir.uitm.edu.my/id/eprint/19099/1/ABS_NORAINI%20SEMAN%20TDRA%20VOL%201%20IGS%2012.pdf Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman. (2012) In: The Doctoral Research Abstracts. IPSis Biannual Publication, 1 (1). Institute of Graduate Studies, UiTM, Shah Alam. |
| spellingShingle | Malaysia Seman, Noraini Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman |
| title | Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman |
| title_full | Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman |
| title_fullStr | Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman |
| title_full_unstemmed | Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman |
| title_short | Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman |
| title_sort | coalition of genetic algorithms and artificial neural network for isolated spoken malay speech recognition / noraini seman |
| topic | Malaysia |
| url | https://ir.uitm.edu.my/id/eprint/19099/1/ABS_NORAINI%20SEMAN%20TDRA%20VOL%201%20IGS%2012.pdf https://ir.uitm.edu.my/id/eprint/19099/ |
| url_provider | http://ir.uitm.edu.my/ |