The comparison of the methods used for the purpose of speaker recognition and parametrizations, when there is a mismatch between training and test conditions due to reverberation, was discussed. Gaussian mixture models (GMM), covariance models, and AR-vector models were used for this purpose. It was fond that the performance of all the methods degrades under reverberation. It was also found that recognition accuracy improved for all the methods when training was performed with reverberant speech prior to testing with minor reverb or major reverb
Speaker recognition is a biometric operation of accepting a claimed person based on analyzing his sp...
Speaker recognition has been developed into a relatively mature state over the past few decades thro...
This work presents an analysis of distant-talking speech recognition in a variety of reverberant con...
Speaker recognition can be used as a security means to authenticate the speaker or as a forensic too...
Automatic speaker recognition systems have developed into an increasingly relevant technology for se...
This communication presents a new method for automatic speech recognition in reverber-ant environmen...
While considerable work has been done to characterize the detrimental effects of channel variability...
Reverberation is a natural phenomenon observed in enclosed environments. It occurs due to the reflec...
The effect of reverberation on speech recognition performance has been investigated in several works...
In this article the authors continue previous studies regarding the investigation of methods that ai...
This work presents an experimental analysis of distant-talking speech recognition in a variety of re...
Speaker recognition has been developed and evolved over the past few decades into a supposedly matur...
This paper proposes two methods for robust automatic speech recognition (ASR) in reverberant environ...
The hypothesis that for a given amount of training data a speaker model has an optimum number of com...
This work analyzes the influence of reverberation on automatic speech recognition (ASR) systems and ...
Speaker recognition is a biometric operation of accepting a claimed person based on analyzing his sp...
Speaker recognition has been developed into a relatively mature state over the past few decades thro...
This work presents an analysis of distant-talking speech recognition in a variety of reverberant con...
Speaker recognition can be used as a security means to authenticate the speaker or as a forensic too...
Automatic speaker recognition systems have developed into an increasingly relevant technology for se...
This communication presents a new method for automatic speech recognition in reverber-ant environmen...
While considerable work has been done to characterize the detrimental effects of channel variability...
Reverberation is a natural phenomenon observed in enclosed environments. It occurs due to the reflec...
The effect of reverberation on speech recognition performance has been investigated in several works...
In this article the authors continue previous studies regarding the investigation of methods that ai...
This work presents an experimental analysis of distant-talking speech recognition in a variety of re...
Speaker recognition has been developed and evolved over the past few decades into a supposedly matur...
This paper proposes two methods for robust automatic speech recognition (ASR) in reverberant environ...
The hypothesis that for a given amount of training data a speaker model has an optimum number of com...
This work analyzes the influence of reverberation on automatic speech recognition (ASR) systems and ...
Speaker recognition is a biometric operation of accepting a claimed person based on analyzing his sp...
Speaker recognition has been developed into a relatively mature state over the past few decades thro...
This work presents an analysis of distant-talking speech recognition in a variety of reverberant con...