Telugu Speech Recognition on LSF and DNN Techniques
This fast world is running with machine and human interaction. This kind of interaction is not an easy task. For proper interaction between human and machine speech recognition is major area where the machine should understand the speech properly to perform the tasks. So ASR have been developed whic...
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| Veröffentlicht in: | International journal of recent technology and engineering 2019-11, Vol.8 (4), p.7160-7162 |
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| container_title | International journal of recent technology and engineering |
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| creator | Sangeetha, Y. Praveen Kumar, Dr. Archek Maheshwari, Neerudu Uma Srinivas, Rodda Jyothi, P. |
| description | This fast world is running with machine and human interaction. This kind of interaction is not an easy task. For proper interaction between human and machine speech recognition is major area where the machine should understand the speech properly to perform the tasks. So ASR have been developed which improvised the HMIS (“Human Machine Interaction systems”) technology in to the deep level. This research focuses on speech recognition over “Telugu language”, which is used in Telugu HMI systems. This paper uses LSF (linear spectral frequencies) technique for feature extraction and DNN for feature classification which finally produced the effective results. Many other recognition systems also used these techniques but for Telugu language this are the most suitable techniques. |
| doi_str_mv | 10.35940/ijrte.D5257.118419 |
| format | Article |
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| identifier | ISSN: 2277-3878 |
| ispartof | International journal of recent technology and engineering, 2019-11, Vol.8 (4), p.7160-7162 |
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| language | eng |
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| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| title | Telugu Speech Recognition on LSF and DNN Techniques |
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