{"id":"https://openalex.org/W2153309934","doi":"https://doi.org/10.1109/icme.2004.1394642","title":"Effective and efficient sports highlights extraction using the minimum description length criterion in selecting GMM structures [audio classification]","display_name":"Effective and efficient sports highlights extraction using the minimum description length criterion in selecting GMM structures [audio classification]","publication_year":2005,"publication_date":"2005-03-21","ids":{"openalex":"https://openalex.org/W2153309934","doi":"https://doi.org/10.1109/icme.2004.1394642","mag":"2153309934"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2004.1394642","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2004.1394642","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054422494","display_name":"Ziyou Xiong","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ziyou Xiong","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080532753","display_name":"R. Radhakrishnan","orcid":"https://orcid.org/0000-0002-9508-5902"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R. Radhakrishnan","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories, Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028124265","display_name":"Ajay Divakaran","orcid":"https://orcid.org/0000-0003-0371-5346"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A. Divakaran","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories, Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101457343","display_name":"T.S. Huang","orcid":"https://orcid.org/0000-0003-1513-1356"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"T.S. Huang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5054422494"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":1.9075,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.86897672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"5","issue":null,"first_page":"1947","last_page":"1950"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.8252654075622559},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7707705497741699},{"id":"https://openalex.org/keywords/minimum-description-length","display_name":"Minimum description length","score":0.6767390370368958},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5836984515190125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5824908018112183},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5770277976989746},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.48455682396888733},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4601519703865051},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.43540772795677185},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4243004024028778},{"id":"https://openalex.org/keywords/audio-signal-processing","display_name":"Audio signal processing","score":0.4148838222026825},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3749375343322754},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3550722599029541},{"id":"https://openalex.org/keywords/audio-signal","display_name":"Audio signal","score":0.23420405387878418},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.13301092386245728}],"concepts":[{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.8252654075622559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7707705497741699},{"id":"https://openalex.org/C87465248","wikidata":"https://www.wikidata.org/wiki/Q1417790","display_name":"Minimum description length","level":2,"score":0.6767390370368958},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5836984515190125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5824908018112183},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5770277976989746},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.48455682396888733},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4601519703865051},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.43540772795677185},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4243004024028778},{"id":"https://openalex.org/C127220857","wikidata":"https://www.wikidata.org/wiki/Q2719318","display_name":"Audio signal processing","level":4,"score":0.4148838222026825},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3749375343322754},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3550722599029541},{"id":"https://openalex.org/C64922751","wikidata":"https://www.wikidata.org/wiki/Q4650799","display_name":"Audio signal","level":3,"score":0.23420405387878418},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.13301092386245728},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2004.1394642","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2004.1394642","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W79749824","https://openalex.org/W2074392550","https://openalex.org/W2106596127","https://openalex.org/W2143800062","https://openalex.org/W2154458328","https://openalex.org/W4247035037","https://openalex.org/W6603244412","https://openalex.org/W6624852173","https://openalex.org/W6669262714"],"related_works":["https://openalex.org/W4298831272","https://openalex.org/W2962916388","https://openalex.org/W2086694237","https://openalex.org/W2095614499","https://openalex.org/W1965383186","https://openalex.org/W1853799209","https://openalex.org/W1992295166","https://openalex.org/W2153309934","https://openalex.org/W2143508933","https://openalex.org/W4312179141"],"abstract_inverted_index":{"In":[0],"fitting":[1],"the":[2,14,33,42,67],"training":[3],"data":[4],"with":[5,28],"Gaussian":[6],"mixture":[7],"models":[8],"(GMMs)":[9],"of":[10,69,73],"appropriate":[11],"structures":[12,75],"using":[13],"MDL":[15],"(minimum":[16],"description":[17],"length)":[18],"criterion,":[19],"we":[20,35,49],"are":[21,36],"able":[22,38],"to":[23,39,59],"improve":[24,41],"audio":[25,53],"classification":[26],"accuracy":[27,43],"a":[29,70,78],"large":[30],"margin.":[31],"With":[32],"MDL-GMMs,":[34],"also":[37],"greatly":[40],"in":[44,76],"extracting":[45],"sports":[46],"highlights.":[47],"Since":[48],"have":[50,65],"focused":[51],"on":[52],"domain":[54],"processing,":[55],"it":[56],"enables":[57],"us":[58],"extract":[60],"highlights":[61],"very":[62],"quickly.":[63],"We":[64],"demonstrated":[66],"importance":[68],"better":[71],"understanding":[72],"model":[74],"such":[77],"pattern":[79],"recognition":[80],"task.":[81]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}