A Quantitative Study of the Automatic Speech Recognition Technique
Anchal Kaytal1, Amanpreet Kaur2
1Anchal Kaytal, M.Tech, Department of CSE, RIMT, Mandi Gobindgarh (Punjab), India.
2Amanpreet Kaur, Assistant Professor, RIMT, Mandi Gobindgarh (Punjab), India.
Manuscript received on 10 November 2013 | Revised Manuscript received on 18 November 2013 | Manuscript Published on 30 November 2013 | PP: 84-87 | Volume-3 Issue-6, November 2013 | Retrieval Number: F1343113613/13©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© 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: In the last two decades, few researchers have worked for the development of Automatic Speech Recognition Systems for most of these languages in such a way that development of this technology can reach at par with the research work which has been done and is being done for the different languages in the rest of the world. Punjabi is the 10th most widely spoken language in the world for which no considerable work has been done in this area of automatic speech recognition. Being a member of Indo-Aryan languages family and a language rich in literature, Punjabi language deserves attention in this highly growing field of Automatic speech recognition. The Speech is most prominent & primary mode of Communication among of human being. Today, speech technologies are commercially available for an unlimited but interesting range of tasks. These technologies enable machines to respond correctly and reliably to human voices, and provide useful and valuable services.
Keywords: ASR, Punjabi Speech Recognition, Recognition Techniques.
Scope of the Article: Pattern Recognition