Detection and Identification of Rare Audio-visual Cues - DIRAC
Reseach leader:Heřmanský Hynek
Team leaders:Burget Lukáš, Hannemann Mirko, Kombrink Stefan, Mikolov Tomáš
Agency:EU-6FP-IST
Code:027787 - DIRAC
Start:2006
End:2010
Keywords:audio, video, detection
Annotation:
Today's computers can do many amazing things but there are still many "trivial" but important tasks they cannot do well. In particular, current information extraction techniques perform well when event types are well represented in the training data but often fail when encountering information-rich unexpected rare events. DIRAC project addresses this crucial machine weakness and aims at designing and developing an environment-adaptive autonomous artificial cognitive system that will detect, identify and classify possibly threatening rare events from the information derived by multiple active information-seeking audio-visual sensors.

Biological organisms rely for their survival on detecting and identifying new events. DIRAC therefore strives to combine its expertise in physiology of mammalian auditory and visual cortex and in audio/visual recognition engineering with the aim to move the art of audiovisual machine recognition from the classical signal processing/pattern classification paradigm to human-like information extraction. This means, among other things, to move from interpretation of all incoming data to reliable rejection of non-informative inputs, from passive acquisition of a single incoming stream to active search for the most relevant information in multiple streams, and from a system optimized for one static environment to autonomous adaptation to new changing environments, thus forming foundation for a new generation of efficient cognitive information processing technologies.

DIRAC is an EU IP IST project of the 6th Framework Program. Its duration is 5 years, from January 2006 until December 2010.

Partners of the project comes from all over the world and are the following: Idiap Research Institute (coordinator),  Eidgenossische Technische Hochschule Zuerich (CH),  The Hebrew University of Jerusalem (IL),  Czech Technical University (CS), Carl von Ossietzky Universitaet Oldenburg (DE), Leibniz Institute for Neurobiology (DE), Katholieke Universiteit Leuven (B), Oregon Health and Science University OGI School of Science and Engineerring (USA).

Products

Publications

2012Kombrink, S., Hannemann, M., Burget, L.: Out-of-Vocabulary Word Detection and Beyond, Detection and Identification of Rare Audiovisual Cues, Springer-Verlag Berlin Heidelberg, DE, Springer, 2012, p. 57-65, ISBN 978-3-642-24033-1
2011Deoras, A., Mikolov, T., Kombrink, S., Karafiát, M., Khudanpur, S.: Variational Approximation of Long-span Language Models for LVCSR, In: Proceedings of the 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, Praha, CZ, IEEESP, 2011, p. 5532-5535, ISBN 978-1-4577-0537-3
 Kombrink, S., Mikolov, T.: Recurrent Neural Network Language Modeling Applied to the Brno AMI/AMIDA 2009 Meeting Recognizer Setup, In: Proceedings of the 17th Conference STUDENT EEICT 2011, Brno, CZ, VUT v Brně, 2011, p. 527-531, ISBN 978-80-214-4273-3
 Mikolov, T., Kombrink, S., Burget, L., Černocký, J., Khudanpur, S.: Extensions of Recurrent Neural Network Language Model, In: Proceedings of the 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, Praha, CZ, IEEESP, 2011, p. 5528-5531, ISBN 978-1-4577-0537-3
2010Černocký, J., Szőke, I., Hannemann, M., Kombrink, S.: Word-subword based keyword spotting with implications in OOV detection, Pacific Grove, US, IEEE, 2010, p. 34
 Hannemann, M., Kombrink, S., Karafiát, M., Burget, L.: Similarity Scoring for Recognizing Repeated Out-of-VocabularyWords, In: Proceedings of the 11th Annual Conference of the International Speech Communication Association (INTERSPEECH 2010), Makuhari, Chiba, JP, ISCA, 2010, p. 897-900, ISBN 978-1-61782-123-3, ISSN 1990-9772
 Kombrink, S., Hannemann, M., Burget, L., Heřmanský, H.: Recovery of Rare Words in Lecture Speech, In: Proc. Text, Speech and Dialogue 2010, Brno, CZ, Springer, 2010, p. 330-337, ISBN 978-3-642-15759-2, ISSN 0302-9743
 Kombrink, S., Hannemann, M., Burget, L.: Out-of-vocabulary word detection and beyond, In: ECML PKDD 2010 Proceedings and Journal Content, Barcelona, ES, 2010, p. 1-8
 Kombrink, S., Hannemann, M.: Final system for identifying unexpected acoustic inputs (BUT), Brno, CZ, EU-6FP-IST, 2010, p. 1-19
 Mikolov, T., Karafiát, M., Burget, L., Černocký, J., Khudanpur, S.: Recurrent neural network based language model, In: Proceedings of the 11th Annual Conference of the International Speech Communication Association (INTERSPEECH 2010), Makuhari, Chiba, JP, ISCA, 2010, p. 1045-1048, ISBN 978-1-61782-123-3, ISSN 1990-9772
2009Brümmer, N., Strasheim, A., Hubeika, V., Matějka, P., Burget, L., Glembek, O.: Discriminative Acoustic Language Recognition via Channel-Compensated GMM Statistics, In: Proc. Interspeech 2009, Brighton, GB, ISCA, 2009, p. 2187-2190, ISSN 1990-9772
 Kombrink, S., Burget, L., Matějka, P., Karafiát, M., Heřmanský, H.: Posterior-based Out of Vocabulary Word Detection in Telephone Speech, In: Proc. Interspeech 2009, Brighton, GB, ISCA, 2009, p. 80-83, ISSN 1990-9772
2008Burget, L., Brümmer, N., Reynolds, D., Kenny, P., Pelecanos, J., Vogt, R., Castaldo, F., Dehak, N., Dehak, R., Glembek, O., Karam, Z., Noecker, J., J., Na, H., Y., Costin, C., C., Hubeika, V., Kajarekar, S., Scheffer, N., Černocký, J.: Robust Speaker Recognition Over Varying Channels, Baltimore, US, JHU, 2008, p. 81
 Burget, L., Schwarz, P., Matějka, P., Hannemann, M., Rastrow, A., White, C., Khudanpur, S., Heřmanský, H., Černocký, J.: Combination of strongly and weakly constrained recognizers for reliable detection of OOVs, In: Proc. International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Las Vegas, US, IEEESP, 2008, p. 4, ISBN 1-4244-1484-9

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