Telugu Speech Recognition on TRI-SPECTRAL and DNN Techniques
Chunchu Raj Kumar1, Archek Praveen Kumar2, B Sheha Priya3, Affrose4, A. Haseena5
1Chunchu Raj Kumar, Assistant Professor, Department of ECE, Malla Reddy College of Engineering for Women, Hyderabad, Telangana, India.
2Dr. Archek Praveen Kumar, Professor, HOD, Department of ECE, Malla Reddy College of Engineering for Women, Hyderabad, Telangana, India.
3B Sheha Priya Assistant Professor, Department of ECE, Malla Reddy College of Engineering for Women, Hyderabad, Telangana, India.
4Affrose, Assistant Professor, Department of ECE, Malla Reddy College of Engineering for Women, Hyderabad, Telangana, India.
5A. Haseena, Assistant Professor, Department of ECE, Amity University, Jaipur, Rajasthan, India.
Manuscript received on November 20, 2019. | Revised Manuscript received on November 28, 2019. | Manuscript published on 30 November, 2019. | PP: 7156-7169 | Volume-8 Issue-4, November 2019. | Retrieval Number: D5255118419/2019©BEIESP | DOI: 10.35940/ijrte.D5255.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This Research focus on the recognition of speech signals for Telugu language. The data of Telugu language considered is in isolated format. 10 isolated words are considered which are frequently spoken and recognized. Advanced technique named Tri spectral technique and DNN is used for this recognition. Tri spectral is a feature extraction technique. DNN is a feature classification technique. This research can be used in many interfacing systems which helps the humans to interact with the hardware or software systems easily. Design of ASR (“Automatic Speech Recognition System”) deals with many parameters which should finally conclude with promising recognition results. This techniques used in this research has given a better result with the accuracy of approximately 96.27%.
Keywords: Speech Recognition, Telugu Language, Tri Spectral, DNN.
Scope of the Article: Pattern Recognition.