Challenges in using a Standard Speech Recognition Engine in Small Vocabulary Domain
Narayanan Srinivasan1, S. R.Balasundaram2
1Narayanan Srinivasan, National Institute of Technology, Trichy (Tamil Nadu), India.
2S. R.Balasundaram, National Institute of Technology, Trichy (Tamil Nadu), India.
Manuscript received on 24 August 2019 | Revised Manuscript received on 05 September 2019 | Manuscript Published on 16 September 2019 | PP: 953-958 | Volume-8 Issue-2S6 July 2019 | Retrieval Number: B11820782S619/2019©BEIESP | DOI: 10.35940/ijrte.B1182.0782S619
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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 discusses the challenges and proposes recommendations on using a standard speech recognition engine for a small vocabulary Air Traffic Controller Pilot communication domain. With the given challenges in transcribing the Air Traffic Communication due to the inherent radio issues in cockpit and the con-troller room, gathering the corpus for training the speech recognition model is another important problem. Taking advantage of the maturity of today’s speech recognition systems for the standard English words used in the communication, this paper focusses on the challenges in decoding the domain specific named entity words used in the communication.
Keywords: Air Traffic Speech, Contextual Speech Recognition, Named Entity Recognition, Non-Trained Speech.
Scope of the Article: Pattern Recognition