2014 |
Panagiotis Giannoulis, Gerasimos Potamianos, Athanasios Katsamanis, Petros Maragos Multi-microphone fusion for detection of speech and acoustic events in smart spaces Conference European Signal Processing Conference, 2014, ISSN: 22195491. Abstract | BibTeX | Links: [PDF] @conference{168, title = {Multi-microphone fusion for detection of speech and acoustic events in smart spaces}, author = { Panagiotis Giannoulis and Gerasimos Potamianos and Athanasios Katsamanis and Petros Maragos}, url = {http://robotics.ntua.gr/wp-content/uploads/publications/GiannoulisEtAl_MultimicrFusionDetectionSpeechEventsSmartspaces_EUSIPCO2014.pdf}, issn = {22195491}, year = {2014}, date = {2014-01-01}, booktitle = {European Signal Processing Conference}, pages = {2375--2379}, abstract = {In this paper, we examine the challenging problem of de- tecting acoustic events and voice activity in smart indoors environments, equipped with multiple microphones. In par- ticular, we focus on channel combination strategies, aiming to take advantage of the multiple microphones installed in the smart space, capturing the potentially noisy acoustic scene from the far-field. We propose various such approaches that can be formulated as fusion at the signal, feature, or at the decision level, as well as combinations of the above, also including multi-channel training. We apply our methods on two multi-microphone databases: (a) one recorded inside a small meeting room, containing twelve classes of isolated acoustic events; and (b) a speech corpus containing inter- fering noise sources, simulated inside a smart home with multiple rooms. Our multi-channel approaches demonstrate significant improvements, reaching relative error reductions over a single-channel baseline of 9.3% and 44.8% in the two datasets, respectively.}, keywords = {}, pubstate = {published}, tppubtype = {conference} } In this paper, we examine the challenging problem of de- tecting acoustic events and voice activity in smart indoors environments, equipped with multiple microphones. In par- ticular, we focus on channel combination strategies, aiming to take advantage of the multiple microphones installed in the smart space, capturing the potentially noisy acoustic scene from the far-field. We propose various such approaches that can be formulated as fusion at the signal, feature, or at the decision level, as well as combinations of the above, also including multi-channel training. We apply our methods on two multi-microphone databases: (a) one recorded inside a small meeting room, containing twelve classes of isolated acoustic events; and (b) a speech corpus containing inter- fering noise sources, simulated inside a smart home with multiple rooms. Our multi-channel approaches demonstrate significant improvements, reaching relative error reductions over a single-channel baseline of 9.3% and 44.8% in the two datasets, respectively. |
2013 |
I. Rodomagoulakis, P. Giannoulis, Z. I. Skordilis, P. Maragos, G. Potamianos Experiments on far-field multichannel speech processing in smart homes Conference 2013 18th International Conference on Digital Signal Processing, DSP 2013, 2013, ISBN: 9781467358057. @conference{175, title = {Experiments on far-field multichannel speech processing in smart homes}, author = { I. Rodomagoulakis and P. Giannoulis and Z. I. Skordilis and P. Maragos and G. Potamianos}, url = {http://robotics.ntua.gr/wp-content/uploads/publications/RGSMP_ExperimsFarfieldMultichannelSpeechProcessSmartHomes_DSP2013.pdf}, doi = {10.1109/ICDSP.2013.6622707}, isbn = {9781467358057}, year = {2013}, date = {2013-01-01}, booktitle = {2013 18th International Conference on Digital Signal Processing, DSP 2013}, keywords = {}, pubstate = {published}, tppubtype = {conference} } |
Copyright Notice:
Some material presented is available for download to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
The work already published by the IEEE is under its copyright. Personal use of such material is permitted. However, permission to reprint/republish the material for advertising or promotional purposes, or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of the work in other works must be obtained from the IEEE.