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This paper addresses the impact of telephone transmission channels on automatic speech recognition (ASR) performance. A real-time simulation model is described and implemented, which allows impairments that are encountered in traditional as well as modern ...
An HMM-based speaker clustering framework is presented, where the number of speakers and segmentation boundaries are unknown \emph{a priori}. Ideally, the system aims to create one pure cluster for each speaker. The HMM is ergodic in nature with a minimum ...
State transition matrices as used in standard HMM decoders have two widely perceived limitations. One is that the implicit Geometric state duration distributions which they model do not accurately reflect true duration distributions. The other is that they ...
This paper investigates possibilities to automatically find a low-dimensional, formant-related physical representation of the speech signal, which is suitable for automatic speech recognition (ASR). This aim is motivated by the fact that formants have been ...
Traditional microphone array speech recognition systems simply recognise the enhanced output of the array. As the level of signal enhancement depends on the number of microphones, such systems do not achieve acceptable speech recognition performance for ar ...
This paper investigates possibilities to automatically find a low-dimensional, formant-related physical representation of the speech signal, which is suitable for automatic speech recognition (ASR). This aim is motivated by the fact that formants have been ...
In this paper, we present an HMM2 based method for speaker normalization. Introduced as an extension of Hidden Markov Model (HMM), HMM2 differentiates itself from the regular HMM in terms of the emission density modeling, which is done by a set of state-de ...
This paper proposes a novel technique for estimating the signal power spectral density to be used in the transfer function of a microphone array post-filter. The technique is a modification of the existing Zelinski post-filter, which uses the auto- and cro ...
An HMM-based speaker clustering framework is presented, where the number of speakers and segmentation boundaries are unknown \emph{a priori}. Ideally, the system aims to create one pure cluster for each speaker. The HMM is ergodic in nature with a minimum ...
State transition matrices as used in standard HMM decoders have two widely perceived limitations. One is that the implicit Geometric state duration distributions which they model do not accurately reflect true duration distributions. The other is that they ...
