Speaker Recognition in Uncontrolled Environment: A Review
Speaker recognition has been an active research area for many years. Methods to represent and quantify information embedded in speech signal are termed as features of the signal. The features are obtained, modeled and stored for further reference when the system is to be tested. Decision whether to...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2013-03-01
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| Series: | Journal of Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/jisys-2012-0020 |
| Summary: | Speaker recognition has been an active research area for many years. Methods to
represent and quantify information embedded in speech signal are termed as
features of the signal. The features are obtained, modeled and stored for
further reference when the system is to be tested.
Decision whether to accept or reject speakers are taken based on parameters of the data modeling techniques.
Real world offers various degradations to the signal
that hamper the signal quality. The degradations may be due to ambient
background noise, reverberation or multispeaker scenario. This paper
presents a survey of various feature extraction, data modeling methods,
metrics that are used to take the decisions and methods that can be used to
preprocess the degraded data that have been used to perform the task of
speaker recognition. |
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| ISSN: | 0334-1860 2191-026X |