Automatic Speech Recognition: A Review
Anchal Katyal1, Amanpreet Kaur2, Jasmeen Gill3
1Anchal Katyal, M. Tech Scholar (CSE) RIMT, Mandi Gobindgarh, India.
2Ms. Amanpreet Kaur, BBSBEC, (CSE) Fatehgarh Sahib (A.P), India.
3Ms. Jasmeen Gill, RIMT-IET,(CSE) Mandi Gobindgarh,(A.P), India.
Manuscript received on January 25, 2014. | Revised Manuscript received on February 13, 2014. | Manuscript published on February 28, 2014. | PP: 71-74 | Volume-3, Issue-3, February 2014. | Retrieval Number: C2568023314/2013©BEIESP
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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: The research, development and the accuracy of automatic speech recognition (ASR) remains one of the most important research challenges over the years e.g. speaker and language variability, vocabulary size and domain, noise. This paper describes the recent progress and the author’s perspective of ASR and gives an overview of major technological perspective and appreciation of the fundamental progress of Automatic speech recognition.
Keywords: ASR, HMM, Classifications of ASR, Speech Recognition Process, HNN.