Continuous Telugu Speech Recognition On T-LPC and DNN Techniques
N.Uma maheshwari1,. Archek Praveen Kumar2, K. Narmada3, Affrose4, B.Sneha5
1N.Uma maheshwari, Assistant Professor, Department of ECE, Malla Reddy College of Engineering for Women, Telangana, Hyderabad.
2Dr. Archek Praveen Kumar, Professor, HOD, Department of ECE, Malla Reddy College of Engineering for Women, Telangana, Hyderabad.
3K. Narmada, Assistant Professor, Department of ECE, Malla Reddy College of Engineering for Women, Telangana, Hyderabad.
4Affrose, Assistant Professor, Department of ECE, Malla Reddy College of Engineering for Women, Telangana, Hyderabad.
5B.Sneha, Assistant Professor, Department of ECE, Malla Reddy College of Engineering for Women, Telangana, Hyderabad.
Manuscript received on 01 August 2019. | Revised Manuscript received on 06 August 2019. | Manuscript published on 30 September 2019. | PP: 4728-4731 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6856098319/2019©BEIESP | DOI: 10.35940/ijrte.C6856.098319
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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 paper deals with the basic application speech recognition. There are many languages in the world but one of the regional language is Telugu. Recognition of this language helps in many applications for 8 crores of people stay in AP and Telangana states. Recognition is done by recording the speech signals and database creation. Pre-processing is done by 2 stage DNN (seep neural networks) where denoising, framing is done. The preprocessed signal features are extracted using TLPC(teager energy operator linear prediction filter). The features extracted are classified using DNN which generates adequate results. The results are obtained for continuous speech of Telugu language.
Keywords— Continuous Speech Recognition, Telugu Language, T-LPC, DNN.
Scope of the Article: Signal and Speech Processing