An HMM-Based Subband Processing Approach to Speaker Identification

Higgins, Jonathan E.; Damper, R. I.

doi:10.1007/3-540-45344-x_24

Cited by 2 publications

(1 citation statement)

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“…Auto matic speaker recognition is a vital, progressing technology with several possible applications in commerce and business, security, surveillance, etc [7] and it has been an extensive area of research [9]. Recogn ition systems that associate with obtaining the individuality of the person speaking [10] be different in their approach to speech knowledge.…”

Section: Introductionmentioning

confidence: 99%

Principal factor analysis and SVM based effective speaker recognition

Rao

Kumar

2012

2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12)

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Speaker recognition is important for successful development of speech recognizers in various real world applications. In this paper, the speaker recognizer was developed using sUable collection of various speakers both male as weD as female with pitch strength as the feature. We proposed Principal Factor Analysis (PFA) technique for dimensionality reduction for accurate speaker recognition system. The first module performs feature extraction from speech samples taking pitch strength as the feature. The second module executes dime-nsionality reduction from the windowing of speech samples, where data samples are normally signified as matrices or higher order tensors. The system was trained by Support Vector Machine (SVM) using dimensionality reduced feature matrix. The implementation results show that the proposed system recognizes whether the given speaker is authorized or not.

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Section: Introductionmentioning

confidence: 99%