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An audio-visual corpus for multimodal automatic speech recognition

Abstract

review of available audio-visual speech corpora and a description of a new multimodal corpus of English speech recordings is provided. The new corpus containing 31 hours of recordings was created specifically to assist audio-visual speech recognition systems (AVSR) development. The database related to the corpus includes high-resolution, high-framerate stereoscopic video streams from RGB cameras, depth imaging stream utilizing Time-of-Flight camera accompanied by audio recorded using both: a microphone array and a microphone built in a mobile computer. For the purpose of applications related to AVSR systems training, every utterance was manually labeled, resulting in label files added to the corpus repository. Owing to the inclusion of recordings made in noisy conditions the elaborated corpus can also be used for testing robustness of speech recognition systems in the presence of acoustic background noise. The process of building the corpus, including the recording, labeling and post-processing phases is described in the paper. Results achieved with the developed audio-visual automatic speech recognition (ASR) engine trained and tested with the material contained in the corpus are presented and discussed together with comparative test results employing a state-of-the-art/commercial ASR engine. In order to demonstrate the practical use of the corpus it is made available for the public use.

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Details

Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
JOURNAL OF INTELLIGENT INFORMATION SYSTEMS no. 49, pages 167 - 192,
ISSN: 0925-9902
Language:
English
Publication year:
2017
Bibliographic description:
Czyżewski A., Kostek B., Bratoszewski P., Kotus J., Szykulski M.: An audio-visual corpus for multimodal automatic speech recognition// JOURNAL OF INTELLIGENT INFORMATION SYSTEMS. -Vol. 49, nr. 2 (2017), s.167-192
DOI:
Digital Object Identifier (open in new tab) 10.1007/s10844-016-0438-z
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