Nusrat Jahan, Md. Ashikur Rahman Khan, Zayed Us Salehin, Nishu Nath
Automatic speech recognition translates spoken words into the text; It is still a challenging task due to the high viability in speech signals. Several decoding algorithms and recognition systems have been developed, aimed at various recognition tasks. The design of the speech recognition system requires careful attention to the challenges or issue such as various types of speech classes, speech representation, feature extraction techniques, database and performance evaluation. This paper presents a study of basic approaches to speech recognition and also presents an error analysis of existing speech recognition system to provide a better system.
Hidden Markov model, Acoustic model, language model, Feature Extraction, Google Web Speech API, Voice Notepad
Cite this paper
Nusrat Jahan, Md. Ashikur Rahman Khan, Zayed Us Salehin, Nishu Nath. (2022) An Efficient Method for Improving Automatic Speech Recognition. International Journal of Computers, 7, 19-26