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This paper proposes a feature integration framework for heart sound biometric applications. The method selects the best features of different sound classification systems into a unique heart sound biometric system. The framework is developed and tested for both user identification and verification tasks. The experimental results show significant improvements in performance of the proposed system over...
This paper proposes a novel system for sound event classification based on Feature Integration, Recursive Feature Elimination Support Vector Machine (RFESVM) and Structured Classification. The key points of the proposed method can be summarized as follows: 1) the integration of various feature extraction methods coming from different research communities in one system; 2) the use of feature selection...
This paper presents a strategy to optimize the phonotactic front-end for spoken language recognition. This is achieved by selecting a subset of phones from an existing phone recognizer's phone inventory such that only the phones that best discriminate each of the target languages are selected. Each such phone subset will be used to construct a target-oriented phone tokenizer (TOPT). In this study,...
In this paper, a new feature selection method for speaker recognition is proposed to keep the high quality speech frames for speaker modelling and to remove noisy and corrupted speech frames. In order to obtain robust voice activity detection in variety of acoustic conditions, the spectral subtraction algorithm is adopted to estimate the frame power. An energy based frame selection algorithm is then...
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