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A Survey of Speaker Recognition: Fundamental Theories, Recognition Methods and Opportunities
- Source :
- IEEE Access, Vol 9, Pp 79236-79263 (2021)
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- Humans can identify a speaker by listening to their voice, over the telephone, or on any digital devices. Acquiring this congenital human competency, authentication technologies based on voice biometrics, such as automatic speaker recognition (ASR), have been introduced. An ASR recognizes speakers by analyzing speech signals and characteristics extracted from speaker’s voices. ASR has recently become an effective research area as an essential aspect of voice biometrics. Specifically, this literature survey gives a concise introduction to ASR and provides an overview of the general architectures dealing with speaker recognition technologies, and upholds the past, present, and future research trends in this area. This paper briefly describes all the main aspects of ASR, such as speaker identification, verification, diarization etc. Further, the performance of current speaker recognition systems are investigated in this survey with the limitations and possible ways of improvement. Finally, a few unsolved challenges of speaker recognition are presented at the closure of this survey.
- Subjects :
- General Computer Science
Computer science
Speech recognition
Feature extraction
challenges
02 engineering and technology
030507 speech-language pathology & audiology
03 medical and health sciences
0202 electrical engineering, electronic engineering, information engineering
General Materials Science
Active listening
Electrical and Electronic Engineering
Closure (psychology)
recognition techniques
Authentication
business.industry
feature extraction
Deep learning
General Engineering
020206 networking & telecommunications
Automatic speaker recognition
performance measures
Speaker recognition
TK1-9971
Speaker diarisation
Electrical engineering. Electronics. Nuclear engineering
Artificial intelligence
0305 other medical science
business
Literature survey
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....8e4657414cb49c032134ba5422450a6b
- Full Text :
- https://doi.org/10.1109/access.2021.3084299