Automatic Speech Recognition Using Limited Vocabulary: A Survey

被引:13
|
作者
Fendji, Jean Louis K. E. [1 ]
Tala, Diane C. M. [2 ]
Yenke, Blaise O. [1 ]
Atemkeng, Marcellin [3 ]
机构
[1] Univ Ngaoundere, Univ Inst Technol, Dept Comp Engn, Ngaoundere 455, Cameroon
[2] Univ Ngaoundere, Fac Sci, Dept Math & Comp Sci, Ngaoundere, Cameroon
[3] Rhodes Univ, Dept Math, ZA-6140 Grahamstown, South Africa
关键词
NEURAL-NETWORKS; SYSTEM; ALGORITHM; MODELS;
D O I
10.1080/08839514.2022.2095039
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页数:35
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