Affiliations: [a] Department of Computer Science and Engineering, Chandigarh University, Mohali, Punjab, India | [b] Department of Computer Science and Engineering, Pandit Deendayal Energy University, Gandhinagar, Gujarat, India
Correspondence:
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Corresponding author: Rakesh Kumar, Department of Computer Science and Engineering, Chandigarh University, Mohali, Punjab, India. E-mail: rakesh77kumar@gmail.com.
Abstract: Speech Recognition is one of the prominent research topics in the field of Natural Language Processing (NLP). The Speech Recognition technique removes the barriers and makes the system ease for inter-communication between human beings and devices. The aim of this study is to analyze the Automatic Speech Recognition System (ASRS) proposed by different researchers using Machine learning and Deep Learning techniques. In this work, Indian and foreign languages speech recognition systems like Hindi, Marathi, Malayalam, Urdu, Sanskrit, Nepali, Kannada, Chinese, Japanese, Arabic, Italian, Turkish, French, and German are considered. An integrated framework is presented and elaborated with recent advancement. The various platform like Hidden Markov Model Toolkit (HMM Toolkit), CMU Sphinx, Kaldi toolkit are explained which is used for building the speech recognition model. Further, some applications are elaborated which depict the uses of ASRS.
Keywords: ASRS, deep learning, HMM toolkit, CMU Sphinx, Kaldi toolkit
