Speaker diarization of spontaneous meeting room conversations
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In this paper, we present a method for integrating possible prior knowledge (such as phonetic and lexical knowledge), as well as acoustic context (e.g., the whole utterance) in the phone posterior estimation, and we propose to use the obtained posteriors a ...
The use of local phoneme posterior probabilities has been increasingly explored for improving speech recognition systems. Hybrid hidden Markov model / artificial neural network (HMM/ANN) and Tandem are the most successful examples of such systems. In this ...
The use of local phoneme posterior probabilities has been increasingly explored for improving speech recognition systems. Hybrid hidden Markov model / artificial neural network (HMM/ANN) and Tandem are the most successful examples of such systems. In this ...
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 ...
This paper present a principled SVM based speaker verification system. We propose a new framework and a new sequence kernel that can make use of any Mercer kernel at the frame level. An extension of the sequence kernel based on the Max operator is also pro ...
This paper presents an effective implementation of detection-localization of multiple speech sources with microphone arrays. In particular, the Scaled Conjugate Gradient descent is used for fast and precise localization, within a pre-detected volume of spa ...
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 address issues for improving hands-free speech recognition performance in the presence of multiple simultaneous speakers using multiple distant microphones. In this paper, a log spectral mapping is proposed to estimate the log mel-filterbank outputs of ...
This paper investigates a multilayer perceptron (MLP) based acoustic feature mapping to extract robust features for automatic speech recognition (ASR) of overlapping speech. The MLP is trained to learn the mapping from log mel filter bank energies (MFBEs) ...
In this paper we present a study of automatic speech recognition systems using context-dependent phonemes and graphemes as sub-word units based on the conventional HMM/GMM system as well as tandem system. Experimental studies conducted on three different c ...