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We propose a new auditory inspired feature extraction technique for automatic speech recognition (ASR). Features are extracted by filtering the temporal trajectory of spectral energies in each critical band of speech by a bank of finite impulse response (F ...
This is the first book dedicated to uniting research related to speech and speaker recognition based on the recent advances in large margin and kernel methods. The first part of the book presents theoretical and practical foundations of large margin and ke ...
In this paper we investigate combination of neural net based classifiers using Dempster-Shafer Theory of Evidence. Under some assumptions, combination rule resembles a product of errors rule observed in human speech perception. Different combination are te ...
We investigate the detection of spoken terms in conversational speech using phoneme recognition with the objective of achieving smaller index size as well as faster search speed. Speech is processed and indexed as a sequence of one best phoneme sequence. W ...
We propose a new auditory inspired feature extraction technique for automatic speech recognition (ASR). Features are extracted by filtering the temporal trajectory of spectral energies in each critical band of speech by a bank of finite impulse response (F ...
The goal of this work is to provide robust and accurate speech detection for automatic speech recognition (ASR) in meeting room settings. The solution is based on computing long-term modulation spectrum, and examining specific frequency range for dominant ...
Accurate detection, localization and tracking of multiple moving speakers permits a wide spectrum of applications. Techniques are required that are versatile, robust to environmental variations, and not constraining for non-technical end-users. Based on di ...
We investigate the detection of spoken terms in conversational speech using phoneme recognition with the objective of achieving smaller index size as well as faster search speed. Speech is processed and indexed as a sequence of one best phoneme sequence. W ...
We address the problem of keyword spotting in continuous speech streams when training and testing conditions can be different. We propose a keyword spotting algorithm based on sparse representation of speech signals in a time-frequency feature space. The t ...
Conventional frequency-domain speech enhancement filters improve signal-to-noise ratio (SNR), but also produce speech distortions. This paper describes a novel post-processing algorithm devised for the improvement of the quality of the speech processed by ...