Littérature scientifique sur le sujet « Ad hoc microphone arrays »
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Articles de revues sur le sujet "Ad hoc microphone arrays"
Liaquat, Muhammad Usman, Hafiz Suliman Munawar, Amna Rahman, Zakria Qadir, Abbas Z. Kouzani et M. A. Parvez Mahmud. « Sound Localization for Ad-Hoc Microphone Arrays ». Energies 14, no 12 (10 juin 2021) : 3446. http://dx.doi.org/10.3390/en14123446.
Texte intégralONO, Nobutaka, LE TRUNG Kien, Shigeki MIYABE et Shoji MAKINO. « Ad-hoc Microphone Array ». IEICE ESS Fundamentals Review 7, no 4 (2014) : 336–47. http://dx.doi.org/10.1587/essfr.7.336.
Texte intégralHimawan, I., I. McCowan et S. Sridharan. « Clustered Blind Beamforming From Ad-Hoc Microphone Arrays ». IEEE Transactions on Audio, Speech, and Language Processing 19, no 4 (mai 2011) : 661–76. http://dx.doi.org/10.1109/tasl.2010.2055560.
Texte intégralHahmann, Manuel, Efren Fernandez-Grande, Henrry Gunawan et Peter Gerstoft. « Sound source localization using multiple ad hoc distributed microphone arrays ». JASA Express Letters 2, no 7 (juillet 2022) : 074801. http://dx.doi.org/10.1121/10.0011811.
Texte intégralTavakoli, Vincent Mohammad, Jesper Rindom Jensen, Mads Graecboll Christensen et Jacob Benesty. « A Framework for Speech Enhancement With Ad Hoc Microphone Arrays ». IEEE/ACM Transactions on Audio, Speech, and Language Processing 24, no 6 (juin 2016) : 1038–51. http://dx.doi.org/10.1109/taslp.2016.2537202.
Texte intégralLiaquat, Muhammad Usman, Hafiz Suliman Munawar, Amna Rahman, Zakria Qadir, Abbas Z. Kouzani et M. A. Parvez Mahmud. « Localization of Sound Sources : A Systematic Review ». Energies 14, no 13 (29 juin 2021) : 3910. http://dx.doi.org/10.3390/en14133910.
Texte intégralBertrand, Alexander, Simon Doclo, Sharon Gannot, Nobutaka Ono et Toon van Waterschoot. « Special issue on wireless acoustic sensor networks and ad hoc microphone arrays ». Signal Processing 107 (février 2015) : 1–3. http://dx.doi.org/10.1016/j.sigpro.2014.10.001.
Texte intégralTaghizadeh, Mohammad J., Philip N. Garner et Hervé Bourlard. « Enhanced diffuse field model for ad hoc microphone array calibration ». Signal Processing 101 (août 2014) : 242–55. http://dx.doi.org/10.1016/j.sigpro.2014.02.012.
Texte intégralTaghizadeh, Mohammad J., Reza Parhizkar, Philip N. Garner, Hervé Bourlard et Afsaneh Asaei. « Ad hoc microphone array calibration : Euclidean distance matrix completion algorithm and theoretical guarantees ». Signal Processing 107 (février 2015) : 123–40. http://dx.doi.org/10.1016/j.sigpro.2014.07.016.
Texte intégralPertila, Pasi, Matti S. Hamalainen et Mikael Mieskolainen. « Passive Temporal Offset Estimation of Multichannel Recordings of an Ad-Hoc Microphone Array ». IEEE Transactions on Audio, Speech, and Language Processing 21, no 11 (novembre 2013) : 2393–402. http://dx.doi.org/10.1109/taslp.2013.2286921.
Texte intégralThèses sur le sujet "Ad hoc microphone arrays"
Himawan, Ivan. « Speech recognition using ad-hoc microphone arrays ». Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/34461/1/Ivan_Himawan_Thesis.pdf.
Texte intégralGergen, Sebastian [Verfasser], Rainer [Akademischer Betreuer] Martin et Simon [Akademischer Betreuer] Doclo. « Classification of audio sources using ad-hoc microphone arrays / Sebastian Gergen. Gutachter : Rainer Martin ; Simon Doclo ». Bochum : Ruhr-Universität Bochum, 2016. http://d-nb.info/1089006322/34.
Texte intégralFurnon, Nicolas. « Apprentissage profond pour le rehaussement de la parole dans les antennes acoustiques ad-hoc ». Electronic Thesis or Diss., Université de Lorraine, 2021. http://www.theses.fr/2021LORR0277.
Texte intégralMore and more devices we use in our daily life are embedded with one or more microphones so that they can be voice controlled. Put together, these devices can form a so-called ad-hoc microphone array (AHMA). A speech enhancement step is often applied on the recorded signals to optimise the execution of the voice commands. To this effect, AHMAs are of high interest because of their flexible usage, their wide spatial coverage and the diversity of their recordings. However, it is challenging to exploit the potential of mbox{AHMAs} because devices that compose them may move and have a limited power and bandwidth capacity. Because of these limits, the speech enhancement solutions deployed in ``classic'' microphone arrays, relying on a fusion center and high processing loads, cannot be afforded.This thesis combines the modelling power of deep neural networks (DNNs) with the flexibility of use of AHMAs. To this end, we introduce a distributed speech enhancement system, which does not rely on a fusion center. So-called compressed signals are sent among the nodes and convey the spatial information recorded by the whole AHMA, while reducing the bandwidth requirements. DNNs are used to estimate the coefficients of a multichannel Wiener filter. We conduct an empirical analysis of this sytem, both on synthesized and real data, in order to validate its efficiency and to highlight the benefits of jointly using DNNs and distributed speech enhancement algorithms. We show that our system performs comparatively well compared with a state-of-the-art solution, while being more flexible and significantly reducing the computation cost.Besides, we develop our solution to adapt it to the typical usage conditions of mbox{AHMAs}. We study its behaviour when the number of devices in the AHMA varies. We introduce and compare a spatial attention mechanism and a self-attention mechanism. Both mechanisms make our system robust to a varying number of devices. We show that the weights of the self-attention mechanism reveal the utility of the information carried by each signal.We also analyse our system when the signals recorded by different devices are not synchronised. We propose a solution to improve its performance in such conditions by introducing a temporal attention mechanism. We show that this mechanism can help estimating the sampling time offset between the several devices of the AHMA.Lastly, we show that our system is also efficient for source separation. It can efficiently process the spatial information recorded by the whole AHMA in a typical meeting scenario and alleviate the needs of a complex DNN architecture
Dyberg, Karin, et Linda Farman. « Spatial TDMA in Ad Hoc Networks with Antenna Arrays ». Thesis, Linköping University, Department of Science and Technology, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1104.
Texte intégralIn modern military operations the requirements of transmitting large amounts of information have increased substantially during the last decade. This increases the demand for high-capacity radio networks. It is also very important that military decisions are made on recent and correct information and this implies that low and known delays are required. The existing military radio ommunications, within the Swedish army, do not meet the requirements for capacity and delay.
We have investigated how the capacity and average delay can be improved in an Ad Hoc network with STDMA by using antenna arrays. The study is based on different antenna combinations consistingof single isotropic antenna element, beam steering and adaptive beamforming. We have also studied how the number of antenna elements, the terrain, and an increased connectivity due to the antenna arrays_affects the performance measurements.
The study shows that the capacity is improved with up to 1200%, and the average delays are decreased when using antenna arrays instead of single isotropic antenna elements. Depending on the beamforming combination used the capacity gain and average delay reduction will differ. The way of using the antenna array also affects the capacity gain and average delay. The capacity gain is higher when the antenna array is used not only to suppress and decrease interferences, but also to increase the connectivity.
The study also shows that the capacity gain is higher when using more antenna elements for a network with a high number of links, than with fewer. The benefit from antenna arrays is higher in a flat terrain than in a rough.
Krishnamurthy, Siddhartha. « Peak Sidelobe Level Distribution Computation for Ad Hoc Arrays using Extreme Value Theory ». Thesis, Harvard University, 2014. http://dissertations.umi.com/gsas.harvard:11300.
Texte intégralEngineering and Applied Sciences
Fahmy, Nader S. Todd Terence D. « Ad hoc networks with power-controlled multi-antenna systems : MAC protocols and multihop relaying applications ». *McMaster only, 2005.
Trouver le texte intégralThanayankizil, Lakshmi V. « Opportunistic large array concentric routing algorithm (OLACRA) for upstream routing in wireless sensor networks ». Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26672.
Texte intégralCommittee Chair: Ingram, Mary Ann; Committee Member: Blough, Douglas; Committee Member: Sivakumar, Raghupathy. Part of the SMARTech Electronic Thesis and Dissertation Collection.
Thanayankizil, Lakshmi. « Opportunistic large array (OLA)-based routing for sensor and adhoc wireless networks ». Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50374.
Texte intégralBuchanan, Kristopher Ryan. « A Study Of Aperiodic (Random) Arrays of Various Geometries ». Thesis, 2011. http://hdl.handle.net/1969.1/ETD-TAMU-2011-05-9415.
Texte intégralChapitres de livres sur le sujet "Ad hoc microphone arrays"
Fahmy, Nader S., et Terence D. Todd. « Media Access Control for Ad Hoc Networks with Adaptive Antenna Arrays ». Dans Adaptive Antenna Arrays, 536–52. Berlin, Heidelberg : Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-05592-2_30.
Texte intégralAmilon, Jesper, Zafer Esen, Dilian Gurov, Christian Lidström et Philipp Rümmer. « Automatic Program Instrumentation for Automatic Verification ». Dans Computer Aided Verification, 281–304. Cham : Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37709-9_14.
Texte intégralDyadyuk, Val, Xiaojing Huang, Leigh Stokes, Joseph Pathikulangara, Andrew R., Nasiha Nikolic, John D. et Y. Jay. « Adaptive Antenna Arrays for Ad-Hoc Millimetre-Wave Wireless Communications ». Dans Advanced Trends in Wireless Communications. InTech, 2011. http://dx.doi.org/10.5772/16000.
Texte intégralBeato, Miguel, Reyes Candau, Sebastian Chávez, Christian Möws, et Mathias Truss. « Role of a positioned nucleosome in constitutive repression and hormone induction of the MMTV promoter ». Dans Nuclear Organization, Chromatin Structure, and Gene Expression, 19–39. Oxford University PressOxford, 1997. http://dx.doi.org/10.1093/oso/9780198549239.003.0002.
Texte intégralActes de conférences sur le sujet "Ad hoc microphone arrays"
Gaubitch, Nikolay D., W. Bastiaan Kleijn et Richard Heusdens. « Auto-localization in ad-hoc microphone arrays ». Dans ICASSP 2013 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2013. http://dx.doi.org/10.1109/icassp.2013.6637618.
Texte intégralWang, Dongmei, Takuya Yoshioka, Zhuo Chen, Xiaofei Wang, Tianyan Zhou et Zhong Meng. « Continuous Speech Separation with Ad Hoc Microphone Arrays ». Dans 2021 29th European Signal Processing Conference (EUSIPCO). IEEE, 2021. http://dx.doi.org/10.23919/eusipco54536.2021.9616142.
Texte intégralHon, Tsz-Kin, Lin Wang, Joshua D. Reiss et Andrea Cavallaro. « Fine landmark-based synchronization of ad-hoc microphone arrays ». Dans 2015 23rd European Signal Processing Conference (EUSIPCO). IEEE, 2015. http://dx.doi.org/10.1109/eusipco.2015.7362600.
Texte intégralPasha, Shahab, et Christian Ritz. « Clustered multi-channel dereverberation for ad-hoc microphone arrays ». Dans 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA). IEEE, 2015. http://dx.doi.org/10.1109/apsipa.2015.7415519.
Texte intégralTaghizadeh, Mohammad J., Afsaneh Asaei, Philip N. Garner et Herve Bourlard. « Ad-hoc microphone array calibration from partial distance measurements ». Dans 2014 4th Joint Workshop on Hands-free Speech Communication and Microphone Arrays (HSCMA). IEEE, 2014. http://dx.doi.org/10.1109/hscma.2014.6843239.
Texte intégralChen, Minghua, Zicheng Liu, Li-Wei He, Phil Chou et Zhengyou Zhang. « Energy-Based Position Estimation of Microphones and Speakers for Ad Hoc Microphone Arrays ». Dans 2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. IEEE, 2007. http://dx.doi.org/10.1109/aspaa.2007.4393035.
Texte intégralHennecke, Marius H., et Gernot A. Fink. « Towards acoustic self-localization of ad hoc smartphone arrays ». Dans 2011 Joint Workshop on Hands-free Speech Communication and Microphone Arrays (HSCMA 2011). IEEE, 2011. http://dx.doi.org/10.1109/hscma.2011.5942378.
Texte intégralTavakoli, Vincent M., Jesper R. Jensen, Richard Heusdens, Jacob Benesty et Mads G. Christensen. « Distributed max-SINR speech enhancement with ad hoc microphone arrays ». Dans 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2017. http://dx.doi.org/10.1109/icassp.2017.7952136.
Texte intégralZhang, Yang, Dinei Florêncio et Mark Hasegawa-Johnson. « Glottal Model Based Speech Beamforming for ad-hoc Microphone Arrays ». Dans Interspeech 2017. ISCA : ISCA, 2017. http://dx.doi.org/10.21437/interspeech.2017-1659.
Texte intégralHimawan, Ivan, Iain McCowan et Sridha Sridharan. « Clustering of ad-hoc microphone arrays for robust blind beamforming ». Dans 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2010. http://dx.doi.org/10.1109/icassp.2010.5496201.
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