High Level Speaker Specific Features as an Efficiency Enhancing Parameters in Speaker Recognition System
نویسندگان
چکیده
منابع مشابه
Speaker Recognition System for Limited Speech Data Using High-Level Speaker Specific Features and Support Vector Machines
High-level speaker-specific features (HLSSFs), such as the style of pronunciation of words, their use, phonotactics and prosody, form the main subjects of state-of-the-art research on automatic speaker recognition (ASR). In this paper, we experimentally verify HLSSF extraction and support vector machine (SVM)-based modelling techniques. The HLSSF extraction produces patterns of symbols for each...
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The area of automatic speaker recognition has been dominated by systems using only short-term, low-level acoustic information, such as cepstral features. While these systems have produced low error rates, they ignore higher levels of information beyond low-level acoustics that convey speaker information. Recently published works have demonstrated that such high-level information can be used suc...
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Bottleneck neural networks have recently found success in a variety of speech recognition tasks. This paper presents an approach in which they are utilized in the front-end of a speaker recognition system. The network inputs are melfrequency cepstral coefficients (MFCCs) from multiple consecutive frames and the outputs are speaker labels. We propose using a recording-level criterion that is opt...
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ژورنال
عنوان ژورنال: International Journal of Electrical and Computer Engineering (IJECE)
سال: 2019
ISSN: 2088-8708,2088-8708
DOI: 10.11591/ijece.v9i4.pp2443-2450