Academic Journal
Speech-assisted intelligent software architecture based on deep game neural network.
| Τίτλος: | Speech-assisted intelligent software architecture based on deep game neural network. |
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| Συγγραφείς: | Li, Yue |
| Πηγή: | International Journal of Speech Technology; Mar2021, Vol. 24 Issue 1, p57-66, 10p |
| Θεματικοί όροι: | Automatic speech recognition, Speech processing systems, Software architecture, Speech perception, Singular value decomposition, Feature extraction |
| Περίληψη: | With the rapid development of Internet technology, network assisted instruction system develops rapidly. Speech recognition is a technology that transforms the speech from human beings into words or symbols. From the acoustic feature extraction 40 years ago to the automatic speech recognition system based on deep neural network, speech recognition technology has been gradually improved. Speech recognition algorithm based on neural network has great potential and is an effective way to solve the bottleneck problem of existing speech recognition algorithm. In this paper, the deep neural network and game theory are combined to reduce the dimension of the model by singular value decomposition and reconstruction, in order to reduce the amount of data and improve the accuracy of the experiment. The proposed framework is implemented on the Android system to validate the performance. Compared with the state-of-the-art methodologies, the proposed system can effectively recognize the speech information and extract the information structure. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Speech Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Links: – Type: other Text: Availability: 0 CustomLinks: – Url: https://dx.doi.org/doi:10.1007/s10772-020-09722-x Name: EDS - Springer Nature Journals (s7799221) Category: fullText Text: View record at Springer |
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| Items | – Name: Title Label: Title Group: Ti Data: Speech-assisted intelligent software architecture based on deep game neural network. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Li%2C+Yue%22">Li, Yue</searchLink> – Name: TitleSource Label: Source Group: Src Data: International Journal of Speech Technology; Mar2021, Vol. 24 Issue 1, p57-66, 10p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Automatic+speech+recognition%22">Automatic speech recognition</searchLink><br /><searchLink fieldCode="DE" term="%22Speech+processing+systems%22">Speech processing systems</searchLink><br /><searchLink fieldCode="DE" term="%22Software+architecture%22">Software architecture</searchLink><br /><searchLink fieldCode="DE" term="%22Speech+perception%22">Speech perception</searchLink><br /><searchLink fieldCode="DE" term="%22Singular+value+decomposition%22">Singular value decomposition</searchLink><br /><searchLink fieldCode="DE" term="%22Feature+extraction%22">Feature extraction</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: With the rapid development of Internet technology, network assisted instruction system develops rapidly. Speech recognition is a technology that transforms the speech from human beings into words or symbols. From the acoustic feature extraction 40 years ago to the automatic speech recognition system based on deep neural network, speech recognition technology has been gradually improved. Speech recognition algorithm based on neural network has great potential and is an effective way to solve the bottleneck problem of existing speech recognition algorithm. In this paper, the deep neural network and game theory are combined to reduce the dimension of the model by singular value decomposition and reconstruction, in order to reduce the amount of data and improve the accuracy of the experiment. The proposed framework is implemented on the Android system to validate the performance. Compared with the state-of-the-art methodologies, the proposed system can effectively recognize the speech information and extract the information structure. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of International Journal of Speech Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10772-020-09722-x Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 57 Subjects: – SubjectFull: Automatic speech recognition Type: general – SubjectFull: Speech processing systems Type: general – SubjectFull: Software architecture Type: general – SubjectFull: Speech perception Type: general – SubjectFull: Singular value decomposition Type: general – SubjectFull: Feature extraction Type: general Titles: – TitleFull: Speech-assisted intelligent software architecture based on deep game neural network. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Li, Yue IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 13812416 Numbering: – Type: volume Value: 24 – Type: issue Value: 1 Titles: – TitleFull: International Journal of Speech Technology Type: main |
| ResultId | 1 |