Fendji, Jean Louis K. E and Tala, Diane C. M. and Yenke, Blaise O. and Atemkeng, Marcellin (2022) Automatic Speech Recognition Using Limited Vocabulary: A Survey. Applied Artificial Intelligence, 36 (1). ISSN 0883-9514
Automatic Speech Recognition Using Limited Vocabulary A Survey.pdf - Published Version
Download (2MB)
Abstract
Automatic Speech Recognition (ASR) is an active field of research due to its large number of applications and the proliferation of interfaces or computing devices that can support speech processing. However, the bulk of applications are based on well-resourced languages that overshadow under-resourced ones. Yet, ASR represents an undeniable means to promote such languages, especially when designing human-to-human or human-to-machine systems involving illiterate people. An approach to design an ASR system targeting under-resourced languages is to start with a limited vocabulary. ASR using a limited vocabulary is a subset of the speech recognition problem that focuses on the recognition of a small number of words or sentences. This paper aims to provide a comprehensive view of mechanisms behind ASR systems as well as techniques, tools, projects, recent contributions, and possible future directions in ASR using a limited vocabulary. This work consequently provides a way forward when designing an ASR system using limited vocabulary. Although an emphasis is put on limited vocabulary, most of the tools and techniques reported in this survey can be applied to ASR systems in general.
Item Type: | Article |
---|---|
Subjects: | Souths Book > Computer Science |
Depositing User: | Unnamed user with email support@southsbook.com |
Date Deposited: | 14 Jun 2023 11:35 |
Last Modified: | 28 May 2024 06:04 |
URI: | http://research.europeanlibrarypress.com/id/eprint/1187 |