This paper proposes a real-time algorithmic framework for Automatic Speech Recognition (ASR) in presence of multiple sources in reverberated environment. The addressed real-life acoustic scenario definitely asks for a robust signal processing solution to reduce the impact of source mixing and reverberation on ASR performances. Here the authors show how the implemented approach allows to improve recognition accuracies under real-time processing constraints and overlapping distant-talking speakers. A suitable database has been generated on purpose, by adapting an existing large vocabulary continuous speech recognition (LVCSR) corpus to deal with the acoustic conditions under study
In this article the authors continue previous studies regarding the investigation of methods that ai...
A multi-stream framework with deep neural network (DNN) classifiers is applied to improve automatic ...
This paper presents techniques aiming at improving automatic speech recognition (ASR) in single chan...
This paper proposes a real-time algorithmic framework for Automatic Speech Recognition (ASR) in pres...
This paper deals with speech enhancement in noisy reverberated environments where multiple speakers ...
Abstract. Automatic Speech Recognition (ASR) in reverberant rooms can be improved by choosing traini...
This work analyzes the influence of reverberation on automatic speech recognition (ASR) systems and ...
This paper proposes two methods for robust automatic speech recognition (ASR) in reverberant environ...
This paper proposes a real-time speech enhancement framework working in presence of multiple sources...
Automatic Speech Recognition (ASR) engines are extremely susceptible to noise. There is an increasin...
We present single-channel approaches to robust automatic speech recognition (ASR) in reverberant env...
Automatic speech recognition in the presence of non-stationary interference and reverberation remain...
This paper presents an investigation on speech recognition performance in reverberant envi-ronments....
This paper presents a conversational speech recognition system able to operate in non-stationary rev...
Automatic speech recognition in everyday environments must be robust to significant levels of reverb...
In this article the authors continue previous studies regarding the investigation of methods that ai...
A multi-stream framework with deep neural network (DNN) classifiers is applied to improve automatic ...
This paper presents techniques aiming at improving automatic speech recognition (ASR) in single chan...
This paper proposes a real-time algorithmic framework for Automatic Speech Recognition (ASR) in pres...
This paper deals with speech enhancement in noisy reverberated environments where multiple speakers ...
Abstract. Automatic Speech Recognition (ASR) in reverberant rooms can be improved by choosing traini...
This work analyzes the influence of reverberation on automatic speech recognition (ASR) systems and ...
This paper proposes two methods for robust automatic speech recognition (ASR) in reverberant environ...
This paper proposes a real-time speech enhancement framework working in presence of multiple sources...
Automatic Speech Recognition (ASR) engines are extremely susceptible to noise. There is an increasin...
We present single-channel approaches to robust automatic speech recognition (ASR) in reverberant env...
Automatic speech recognition in the presence of non-stationary interference and reverberation remain...
This paper presents an investigation on speech recognition performance in reverberant envi-ronments....
This paper presents a conversational speech recognition system able to operate in non-stationary rev...
Automatic speech recognition in everyday environments must be robust to significant levels of reverb...
In this article the authors continue previous studies regarding the investigation of methods that ai...
A multi-stream framework with deep neural network (DNN) classifiers is applied to improve automatic ...
This paper presents techniques aiming at improving automatic speech recognition (ASR) in single chan...