A study on the challenges and opportunities of speech recognition for Bengali language

• Published in: The Artificial intelligence review Vol. 55; no. 4; pp. 3431 - 3455
• Main Authors: Mridha, M. F., Ohi, Abu Quwsar, Hamid, Md Abdul, Monowar, Muhammad Mostafa
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.04.2022; Springer; Springer Nature B.V
• Subjects: Artificial Intelligence; Automatic speech recognition; Bengali; Computer Science; Human-computer interaction; International languages; Language; Learning strategies; Phonetics; Speech recognition; Voice recognition; Bengali; Phoneme; Language-dependent challenges; Language-independent challenges; Automatic speech recognition; Speech to text
• ISSN: 0269-2821; 1573-7462
• DOI: 10.1007/s10462-021-10083-3

Speech recognition is a fascinating process that offers the opportunity to interact and command the machine in the field of human-computer interactions. Speech recognition is a language-dependent system constructed directly based on the linguistic and textual properties of any language. Automatic speech recognition (ASR) systems are currently being used to translate speech to text flawlessly. Although ASR systems are being strongly executed in international languages, ASR systems’ implementation in the Bengali language has not reached an acceptable state. In this research work, we sedulously disclose the current status of the Bengali ASR system’s research endeavors. In what follows, we acquaint the challenges that are mostly encountered while constructing a Bengali ASR system. We split the challenges into language-dependent and language-independent challenges and guide how the particular complications may be overhauled. Following a rigorous investigation and highlighting the challenges, we conclude that Bengali ASR systems require specific construction of ASR architectures based on the Bengali language’s grammatical and phonetic structure.