A Review on Feature Extraction for Speaker Recognition under Degraded Conditions
| Autor: | Gökay Dişken, Zekeriya Tufekci, Lütfü Saribulut, Ulus Çevik |
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| Rok vydání: | 2016 |
| Předmět: |
Computer science
business.industry Speech recognition Feature extraction 020206 networking & telecommunications Pattern recognition 02 engineering and technology Speaker recognition computer.software_genre Speaker diarisation 030507 speech-language pathology & audiology 03 medical and health sciences Information extraction Robustness (computer science) Vocal effort Cepstrum 0202 electrical engineering electronic engineering information engineering Artificial intelligence Electrical and Electronic Engineering 0305 other medical science business computer Utterance |
| Zdroj: | IETE Technical Review. 34:321-332 |
| ISSN: | 0974-5971 0256-4602 |
| Popis: | Speech is a signal that includes speaker's emotion, characteristic specification, phoneme-information etc. Various methods have been proposed for speaker recognition by extracting specifications of a given utterance. Among them, short-term cepstral features are used excessively in speech, and speaker recognition areas because of their low complexity, and high performance in controlled environments. On the other hand, their performances decrease dramatically under degraded conditions such as channel mismatch, additive noise, emotional variability, etc. In this paper, a literature review on speaker-specific information extraction from speech is presented by considering the latest studies offering solutions to the aforementioned problem. The studies are categorized in three groups considering their robustness against channel mismatch, additive noise, and other degradations such as vocal effort, emotion mismatch, etc. For a more understandable representation, they are also classified into two tables b... |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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