The Experts below are selected from a list of 137178 Experts worldwide ranked by ideXlab platform
Alexander Waibel - One of the best experts on this subject based on the ideXlab platform.
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DAGM-Symposium - Large Vocabulary Audio-Visual Speech Recognition Using the Janus Speech Recognition Toolkit
Lecture Notes in Computer Science, 2004Co-Authors: Julian Kratt, Florian Metze, Rainer Stiefelhagen, Alexander WaibelAbstract:This paper describes audio-visual Speech Recognition experiments on a multi-speaker, large vocabulary corpus using the Janus Speech Recognition toolkit. We describe a complete audio-visual Speech Recognition system and present experiments on this corpus. By using visual cues as additional input to the Speech recognizer, we observed good improvements, both on clean and noisy Speech in our experiments.
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Large vocabulary audio-visual Speech Recognition using the Janus Speech Recognition toolkit
Pattern Recognition, 2004Co-Authors: Julian Kratt, Florian Metze, Rainer Stiefelhagen, Alexander WaibelAbstract:This paper describes audio-visual Speech Recognition experiments on a multi-speaker, large vocabulary corpus using the Janus Speech Recognition toolkit. We describe a complete audio-visual Speech Recognition system and present experiments on this corpus. By using visual cues as additional input to the Speech recognizer, we observed good improvements, both on clean and noisy Speech in our experiments.
Julian Kratt - One of the best experts on this subject based on the ideXlab platform.
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DAGM-Symposium - Large Vocabulary Audio-Visual Speech Recognition Using the Janus Speech Recognition Toolkit
Lecture Notes in Computer Science, 2004Co-Authors: Julian Kratt, Florian Metze, Rainer Stiefelhagen, Alexander WaibelAbstract:This paper describes audio-visual Speech Recognition experiments on a multi-speaker, large vocabulary corpus using the Janus Speech Recognition toolkit. We describe a complete audio-visual Speech Recognition system and present experiments on this corpus. By using visual cues as additional input to the Speech recognizer, we observed good improvements, both on clean and noisy Speech in our experiments.
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Large vocabulary audio-visual Speech Recognition using the Janus Speech Recognition toolkit
Pattern Recognition, 2004Co-Authors: Julian Kratt, Florian Metze, Rainer Stiefelhagen, Alexander WaibelAbstract:This paper describes audio-visual Speech Recognition experiments on a multi-speaker, large vocabulary corpus using the Janus Speech Recognition toolkit. We describe a complete audio-visual Speech Recognition system and present experiments on this corpus. By using visual cues as additional input to the Speech recognizer, we observed good improvements, both on clean and noisy Speech in our experiments.
Florian Metze - One of the best experts on this subject based on the ideXlab platform.
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DAGM-Symposium - Large Vocabulary Audio-Visual Speech Recognition Using the Janus Speech Recognition Toolkit
Lecture Notes in Computer Science, 2004Co-Authors: Julian Kratt, Florian Metze, Rainer Stiefelhagen, Alexander WaibelAbstract:This paper describes audio-visual Speech Recognition experiments on a multi-speaker, large vocabulary corpus using the Janus Speech Recognition toolkit. We describe a complete audio-visual Speech Recognition system and present experiments on this corpus. By using visual cues as additional input to the Speech recognizer, we observed good improvements, both on clean and noisy Speech in our experiments.
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Large vocabulary audio-visual Speech Recognition using the Janus Speech Recognition toolkit
Pattern Recognition, 2004Co-Authors: Julian Kratt, Florian Metze, Rainer Stiefelhagen, Alexander WaibelAbstract:This paper describes audio-visual Speech Recognition experiments on a multi-speaker, large vocabulary corpus using the Janus Speech Recognition toolkit. We describe a complete audio-visual Speech Recognition system and present experiments on this corpus. By using visual cues as additional input to the Speech recognizer, we observed good improvements, both on clean and noisy Speech in our experiments.
Rainer Stiefelhagen - One of the best experts on this subject based on the ideXlab platform.
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DAGM-Symposium - Large Vocabulary Audio-Visual Speech Recognition Using the Janus Speech Recognition Toolkit
Lecture Notes in Computer Science, 2004Co-Authors: Julian Kratt, Florian Metze, Rainer Stiefelhagen, Alexander WaibelAbstract:This paper describes audio-visual Speech Recognition experiments on a multi-speaker, large vocabulary corpus using the Janus Speech Recognition toolkit. We describe a complete audio-visual Speech Recognition system and present experiments on this corpus. By using visual cues as additional input to the Speech recognizer, we observed good improvements, both on clean and noisy Speech in our experiments.
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Large vocabulary audio-visual Speech Recognition using the Janus Speech Recognition toolkit
Pattern Recognition, 2004Co-Authors: Julian Kratt, Florian Metze, Rainer Stiefelhagen, Alexander WaibelAbstract:This paper describes audio-visual Speech Recognition experiments on a multi-speaker, large vocabulary corpus using the Janus Speech Recognition toolkit. We describe a complete audio-visual Speech Recognition system and present experiments on this corpus. By using visual cues as additional input to the Speech recognizer, we observed good improvements, both on clean and noisy Speech in our experiments.
Gerasimos Potamianos - One of the best experts on this subject based on the ideXlab platform.
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Speech Recognition, Audio-Visual
Encyclopedia of Language & Linguistics, 2006Co-Authors: Gerasimos PotamianosAbstract:Audio-visual Speech Recognition refers to the automatic transcription of Speech into text by exploiting information present in the video of the speaker's mouth region, in addition to the traditionally used acoustic signal. The use of visual information in automatic Speech Recognition is also known as automatic Speechreading or lipreading, and has been motivated by the bimodality of human Speech production and perception, coupled with the fact that audio-only Speech Recognition is not robust in noisy acoustic environments. Audio-visual Speech Recognition systems significantly outperform their audio-only counterparts, especially under ideal visual and noisy audio conditions. Incorporating visual information into Speech Recognition requires two new components: the visual front end, which detects the speaker's mouth area and extracts informative visual Speech features from it, and the integration of the visual features into the Speech Recognition process. The most commonly adopted designs of these components are discussed here.