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Challenges and Limitations in Speech Recognition Technology: A Critical Review of Speech Signal Processing Algorithms, Tools and Systems

Sneha Basak1, Himanshi Agrawal1, Shreya Jena1, Shilpa Gite2,*, Mrinal Bachute2, Biswajeet Pradhan3,4,5,*, Mazen Assiri4
1 Computer Science and Information Technology Department, Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, 412115, India
2 Symbiosis Centre for Applied Artificial Intelligence, Symbiosis International (Deemed University), Pune, 412115, India
3 Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney, New South Wales, 2007, Australia
4 Center of Excellence for Climate Change Research, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
5 Earth Observation Centre, Institute of Climate Change, University Kebangsaan Malaysia, Bangi, Selangor, 43600, Malaysia
* Corresponding Authors: Shilpa Gite. Email: shilpa.gite@sitpune.edu.in; Biswajeet Pradhan. Email: biswajeet.pradhan@uts.edu.au
(This article belongs to this Special Issue: AI-Driven Engineering Applications)

Computer Modeling in Engineering & Sciences https://doi.org/10.32604/cmes.2022.021755

Received 02 February 2022; Accepted 30 June 2022; Published online 23 August 2022


Speech recognition systems have become a unique human-computer interaction (HCI) family. Speech is one of the most naturally developed human abilities; speech signal processing opens up a transparent and hand-free computation experience. This paper aims to present a retrospective yet modern approach to the world of speech recognition systems. The development journey of ASR (Automatic Speech Recognition) has seen quite a few milestones and breakthrough technologies that have been highlighted in this paper. A step-by-step rundown of the fundamental stages in developing speech recognition systems has been presented, along with a brief discussion of various modern-day developments and applications in this domain. This review paper aims to summarize and provide a beginning point for those starting in the vast field of speech signal processing. Since speech recognition has a vast potential in various industries like telecommunication, emotion recognition, healthcare, etc., this review would be helpful to researchers who aim at exploring more applications that society can quickly adopt in future years of evolution.


Speech recognition; automatic speech recognition (ASR); mel-frequency cepstral coefficients (MFCC); hidden Markov model (HMM); artificial neural network (ANN)
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