{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,29]],"date-time":"2025-11-29T07:56:25Z","timestamp":1764402985778,"version":"build-2065373602"},"reference-count":35,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. & Syst."],"published-print":{"date-parts":[[2020,3,1]]},"DOI":"10.1587\/transinf.2019edp7162","type":"journal-article","created":{"date-parts":[[2020,2,29]],"date-time":"2020-02-29T22:10:48Z","timestamp":1583014248000},"page":"631-638","source":"Crossref","is-referenced-by-count":7,"title":["Graph Cepstrum: Spatial Feature Extracted from Partially Connected Microphones"],"prefix":"10.1587","volume":"E103.D","author":[{"given":"Keisuke","family":"IMOTO","sequence":"first","affiliation":[{"name":"Ritsumeikan University"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"publisher","unstructured":"[1] K. Imoto, \u201cIntroduction to acoustic event and scene analysis,\u201d Acoustical Science and Technology, vol.39, no.3, pp.182-188, 2018. 10.1250\/ast.39.182","DOI":"10.1250\/ast.39.182"},{"key":"2","unstructured":"[2] Y. Peng, C. Lin, M. Sun, and K. Tsai, \u201cHealthcare audio event classification using hidden Markov models and hierarchical hidden Markov models,\u201d Proc. IEEE International Conference on Multimedia and Expo (ICME), pp.1218-1221, 2009. 10.1109\/icme.2009.5202720"},{"key":"3","doi-asserted-by":"crossref","unstructured":"[3] P. Guyot, J. Pinquier, and R. Andr\u00e9-Obrecht, \u201cWater sound recognition based on physical models,\u201d Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.793-797, 2013. 10.1109\/icassp.2013.6637757","DOI":"10.1109\/ICASSP.2013.6637757"},{"key":"4","unstructured":"[4] A. Harma, M.F. McKinney, and J. Skowronek, \u201cAutomatic surveillance of the acoustic activity in our living environment,\u201d Proc. IEEE International Conference on Multimedia and Expo (ICME), 2005. 10.1109\/icme.2005.1521503"},{"key":"5","unstructured":"[5] R. Radhakrishnan, A. Divakaran, and P. Smaragdis, \u201cAudio analysis for surveillance applications,\u201d Proc. 2005 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp.158-161, 2005."},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] S. Ntalampiras, I. Potamitis, and N. Fakotakis, \u201cOn acoustic surveillance of hazardous situations,\u201d Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.165-168, 2009. 10.1109\/icassp.2009.4959546","DOI":"10.1109\/ICASSP.2009.4959546"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] A. Eronen, V.T. Peltonen, J.T. Tuomi, A.P. Klapuri, S. Fagerlund, T. Sorsa, G. Lorho, and J. Huopaniemi, \u201cAudio-based context recognition,\u201d IEEE Trans. Audio, Speech, Language Process., vol.14, no.1, pp.321-329, 2006. 10.1109\/tsa.2005.854103","DOI":"10.1109\/TSA.2005.854103"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] K. Imoto and S. Shimauchi, \u201cAcoustic scene analysis based on hierarchical generative model of acoustic event sequence,\u201d IEICE Trans. Inf. & Syst., vol.E99-D, no.10, pp.2539-2549, 2016. 10.1587\/transinf.2016slp0004","DOI":"10.1587\/transinf.2016SLP0004"},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] J. Schr\u00f6der, J. Anemiiller, and S. Goetze, \u201cClassification of human cough signals using spectro-temporal Gabor filterbank features,\u201d Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.6455-6459, 2016. 10.1109\/icassp.2016.7472920","DOI":"10.1109\/ICASSP.2016.7472920"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] T. Zhang and C.J. Kuo, \u201cAudio content analysis for online audiovisual data segmentation and classification,\u201d IEEE Trans. Audio, Speech, Language Process., vol.9, no.4, pp.441-457, 2001.","DOI":"10.1109\/89.917689"},{"key":"11","doi-asserted-by":"crossref","unstructured":"[11] Q. Jin, P.F. Schulam, S. Rawat, S. Burger, D. Ding, and F. Metze, \u201cEvent-based video retrieval using audio,\u201d Proc. INTERSPEECH, 2012.","DOI":"10.21437\/Interspeech.2012-556"},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] Y. Ohishi, D. Mochihashi, T. Matsui, M. Nakano, H. Kameoka, T. Izumitani, and K. Kashino, \u201cBayesian semi-supervised audio event transcription based on Markov Indian buffet process,\u201d Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.3163-3167, 2013. 10.1109\/icassp.2013.6638241","DOI":"10.1109\/ICASSP.2013.6638241"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] J. Liang, L. Jiang, and A. Hauptmann, \u201cTemporal localization of audio events for conflict monitoring in social media,\u201d Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.1597-1601, 2017. 10.1109\/icassp.2017.7952426","DOI":"10.1109\/ICASSP.2017.7952426"},{"key":"14","unstructured":"[14] A. Mesaros, T. Heittola, A. Eronen, and T. Virtanen, \u201cAcoustic event detection in real life recordings,\u201d Proc. 18th European Signal Processing Conference (EUSIPCO), pp.1267-1271, 2010."},{"key":"15","unstructured":"[15] Y. Han, J. Park, and K. Lee, \u201cConvolutional neural networks with binaural representations and background subtraction for acoustic scene classification,\u201d Proc. Detection and Classification of Acoustic Scenes and Events Workshop (DCASE), pp.1-5, 2017."},{"key":"16","unstructured":"[16] H. Jallet, E. \u00c7ak\u0131r, and T. Virtanen, \u201cAcoustic scene classification using convolutional recurrent neural networks,\u201d Proc. Detection and Classification of Acoustic Scenes and Events Workshop (DCASE), pp.1-5, 2017."},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] S. Kim, S. Narayanan, and S. Sundaram, \u201cAcoustic topic models for audio information retrieval,\u201d Proc. 2009 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp.37-40, 2009. 10.1109\/aspaa.2009.5346483","DOI":"10.1109\/ASPAA.2009.5346483"},{"key":"18","doi-asserted-by":"crossref","unstructured":"[18] K. Imoto, Y. Ohishi, H. Uematsu, and H. Ohmuro, \u201cAcoustic scene analysis based on latent acoustic topic and event allocation,\u201d Proc. IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2013. 10.1109\/mlsp.2013.6661957","DOI":"10.1109\/MLSP.2013.6661957"},{"key":"19","doi-asserted-by":"crossref","unstructured":"[19] H. Kwon, H. Krishnamoorthi, V. Berisha, and A. Spanias, \u201cA sensor network for real-time acoustic scene analysis,\u201d Proc. IEEE International Symposium on Circuits and Systems, pp.169-172, 2009. 10.1109\/iscas.2009.5117712","DOI":"10.1109\/ISCAS.2009.5117712"},{"key":"20","doi-asserted-by":"crossref","unstructured":"[20] P. Giannoulis, A. Brutti, M. Matassoni, A. Abad, A. Katsamanis, M. Matos, G. Potamianos, and P. Maragos, \u201cMulti-room speech activity detection using a distributed microphone network in domestic environments,\u201d Proc. 23rd European Signal Processing Conference (EUSIPCO), pp.1271-1275, 2015. 10.1109\/eusipco.2015.7362588","DOI":"10.1109\/EUSIPCO.2015.7362588"},{"key":"21","unstructured":"[21] G. Dekkers, S. Lauwereins, B. Thoen, M.W. Adhana, H.Brouckxon, T. Waterschoot, B. Vanrumste, M. Verhelst, and P.Karsmakers, \u201cThe SINS database for detection of daily activities in a home environment using an acoustic sensor network,\u201d Proc. Detection and Classification of Acoustic Scenes and Events Workshop (DCASE), pp.32-36, 2017."},{"key":"22","unstructured":"[22] G. Dekkers, L. Vuegen, T. Waterschoot, B. Vanrumste, and P. Karsmakers, \u201cDCASE 2018 challenge-task 5: Monitoring of domestic activities based on multi-channel acoustics,\u201d arXiv preprint arXiv:1807.11246, 2018."},{"key":"23","doi-asserted-by":"crossref","unstructured":"[23] R. Tanabe, T. Endo, Y. Nikaido, T. Ichige, P. Nguyen, Y.Kawaguchi, and K. Hamada, \u201cMultichannel acoustic scene classification by blind dereverberation, blind source separation, data augmentation, and model ensembling,\u201d Tech. Rep. DCASE, pp.1-4, 2018.","DOI":"10.1109\/APSIPAASC47483.2019.9023059"},{"key":"24","unstructured":"[24] J. K\u00fcrby, R. Grzeszick, A. Plinge, and G.A. Fink, \u201cBag-of-features acoustic event detection for sensor networks,\u201d Proc. Detection and Classification of Acoustic Scenes and Events Workshop (DCASE), pp.55-59, 2016."},{"key":"25","doi-asserted-by":"crossref","unstructured":"[25] K. Imoto and N. Ono, \u201cSpatial-feature-based acoustic scene analysis using distributed microphone array,\u201d Proc. European Signal Processing Conference (EUSIPCO), pp.739-743, 2015. 10.1109\/eusipco.2015.7362480","DOI":"10.1109\/EUSIPCO.2015.7362480"},{"key":"26","doi-asserted-by":"publisher","unstructured":"[26] K. Imoto and N. Ono, \u201cSpatial cepstrum as a spatial feature using distributed microphone array for acoustic scene analysis,\u201d IEEE\/ACM Trans. Audio, Speech, Language Process., vol.25, no.6, pp.1335-1343, 2017. 10.1109\/taslp.2017.2690559","DOI":"10.1109\/TASLP.2017.2690559"},{"key":"27","doi-asserted-by":"crossref","unstructured":"[27] K. Hasegawa, N. Ono, S. Miyabe, and S. Sagayama, \u201cBlind estimation of locations and time offsets for distributed recording devices,\u201d Proc. Latent Variable Analysis and Signal Separation: 9th International Conference, LVA\/ICA 2010, pp.57-64, 2010. 10.1007\/978-3-642-15995-4_8","DOI":"10.1007\/978-3-642-15995-4_8"},{"key":"28","doi-asserted-by":"crossref","unstructured":"[28] N. Ono, H. Kohno, and S. Sagayama, \u201cBlind alignment of asynchronously recorded signals for distributed microphone array,\u201d Proc. Applications of Signal Processing to Audio and Acoustics(WASPAA), pp.161-164, 2009.","DOI":"10.1109\/ASPAA.2009.5346505"},{"key":"29","unstructured":"[29] J. Schmalenstroeer and R. Haeb-Umbach, \u201cSampling rate synchronization in acoustic sensor networks with a pre-trained clock skew error model,\u201d Proc. 21st European Signal Processing Conference (EUSIPCO), pp.1-5, 2013."},{"key":"30","doi-asserted-by":"publisher","unstructured":"[30] S. Miyabe, N. Ono, and S. Makino, \u201cBlind compensation of interchannel sampling frequency mismatch for ad hoc microphone array based on maximum likelihood estimation,\u201d Elsevier Signal Processing, vol.107, pp.185-196, Feb. 2015. 10.1016\/j.sigpro.2014.09.015","DOI":"10.1016\/j.sigpro.2014.09.015"},{"key":"31","doi-asserted-by":"publisher","unstructured":"[31] D.I. Shuman, S.K. Narang, P. Frossard, A. Ortega, and P.Vandergheynst, \u201cThe emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains,\u201d IEEE Signal Process. Mag., vol.30, no.3, pp.83-98, 2013. 10.1109\/msp.2012.2235192","DOI":"10.1109\/MSP.2012.2235192"},{"key":"32","unstructured":"[32] A. Mesaros, T. Heittola, A. Diment, B. Elizalde, A. Shah, E.Vincent, B. Raj, and T. Virtanen, \u201cDCASE 2017 challenge setup: Tasks, datasets and baseline system,\u201d Proc. Detection and Classification of Acoustic Scenes and Events Workshop (DCASE), pp.85-92, 2017."},{"key":"33","doi-asserted-by":"crossref","unstructured":"[33] J.F. Gemmeke, D.P. Ellis, D. Freedman, A. Jansen, W. Lawrence, R.C. Moore, M. Plakal, and M. Ritter, \u201cAudio set: An ontology and human-labeled dataset for audio events,\u201d Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.776-780, 2017. 10.1109\/icassp.2017.7952261","DOI":"10.1109\/ICASSP.2017.7952261"},{"key":"34","doi-asserted-by":"crossref","unstructured":"[34] K. Imoto and N. Ono, \u201cAcoustic scene classification based on generative model of acoustic spatial words for distributed microphone array,\u201d Proc. European Signal Processing Conference (EUSIPCO), pp.2343-2347, 2017. 10.23919\/eusipco.2017.8081616","DOI":"10.23919\/EUSIPCO.2017.8081616"},{"key":"35","unstructured":"[35] G. Golub and C.V. Loan, Matrix Computations, Johns Hopkins University Press, 1996."}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E103.D\/3\/E103.D_2019EDP7162\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T01:11:40Z","timestamp":1665969100000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E103.D\/3\/E103.D_2019EDP7162\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,1]]},"references-count":35,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2020]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2019edp7162","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"type":"print","value":"0916-8532"},{"type":"electronic","value":"1745-1361"}],"subject":[],"published":{"date-parts":[[2020,3,1]]}}}