{"id":"https://openalex.org/W1515103638","doi":"https://doi.org/10.21437/interspeech.2009-336","title":"Factor analysis for audio-based video genre classification","display_name":"Factor analysis for audio-based video genre classification","publication_year":2009,"publication_date":"2009-09-06","ids":{"openalex":"https://openalex.org/W1515103638","doi":"https://doi.org/10.21437/interspeech.2009-336","mag":"1515103638"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2009-336","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2009-336","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2009","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/A5071001941","display_name":"Micka\u00ebl Rouvier","orcid":"https://orcid.org/0000-0003-3541-3385"},"institutions":[{"id":"https://openalex.org/I4210119991","display_name":"Laboratoire Informatique d'Avignon","ror":"https://ror.org/02n399288","country_code":"FR","type":"facility","lineage":["https://openalex.org/I198415970","https://openalex.org/I4210119991"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Mickael Rouvier","raw_affiliation_strings":["Laboratoire Informatique d'Avignon"],"affiliations":[{"raw_affiliation_string":"Laboratoire Informatique d'Avignon","institution_ids":["https://openalex.org/I4210119991"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017334281","display_name":"Driss Matrouf","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119991","display_name":"Laboratoire Informatique d'Avignon","ror":"https://ror.org/02n399288","country_code":"FR","type":"facility","lineage":["https://openalex.org/I198415970","https://openalex.org/I4210119991"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Driss Matrouf","raw_affiliation_strings":["Laboratoire Informatique d'Avignon"],"affiliations":[{"raw_affiliation_string":"Laboratoire Informatique d'Avignon","institution_ids":["https://openalex.org/I4210119991"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050508708","display_name":"Georges Linar\u00e8s","orcid":"https://orcid.org/0000-0001-8049-9056"},"institutions":[{"id":"https://openalex.org/I4210119991","display_name":"Laboratoire Informatique d'Avignon","ror":"https://ror.org/02n399288","country_code":"FR","type":"facility","lineage":["https://openalex.org/I198415970","https://openalex.org/I4210119991"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Georges Linar\u00e8s","raw_affiliation_strings":["Laboratoire Informatique d'Avignon"],"affiliations":[{"raw_affiliation_string":"Laboratoire Informatique d'Avignon","institution_ids":["https://openalex.org/I4210119991"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5071001941"],"corresponding_institution_ids":["https://openalex.org/I4210119991"],"apc_list":null,"apc_paid":null,"fwci":1.0574,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.7377892,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1155","last_page":"1158"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9972000122070312,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.8300355672836304},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.7488040328025818},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6896694302558899},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6744210124015808},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.6278030276298523},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5861597061157227},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5065330266952515},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48161643743515015},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.4738612174987793},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4230361878871918},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4200844466686249},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4155155122280121},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3263574242591858}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8300355672836304},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.7488040328025818},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6896694302558899},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6744210124015808},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.6278030276298523},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5861597061157227},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5065330266952515},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48161643743515015},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.4738612174987793},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4230361878871918},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4200844466686249},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4155155122280121},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3263574242591858},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2009-336","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2009-336","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2009","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W32979931","https://openalex.org/W1563750459","https://openalex.org/W2022035644","https://openalex.org/W2097470427","https://openalex.org/W2100454127","https://openalex.org/W2100969003","https://openalex.org/W2113144451","https://openalex.org/W2121415728","https://openalex.org/W2121750345","https://openalex.org/W2142526407","https://openalex.org/W2147147599","https://openalex.org/W2151920764","https://openalex.org/W2904424563"],"related_works":["https://openalex.org/W1975321310","https://openalex.org/W1952261593","https://openalex.org/W2014494654","https://openalex.org/W2990323019","https://openalex.org/W3130349901","https://openalex.org/W1579833936","https://openalex.org/W2107361128","https://openalex.org/W2095350775","https://openalex.org/W2075383893","https://openalex.org/W2032826752"],"abstract_inverted_index":{"Statistical":[0],"classifiers":[1],"operate":[2],"on":[3,31,82,107],"features":[4,85],"that":[5,97],"generally":[6],"include":[7],"both":[8],"useful":[9],"and":[10,43,53,86,120],"useless":[11,44],"information.":[12],"These":[13],"two":[14],"types":[15,113],"of":[16,64,111,114,157],"information":[17],"are":[18,98,105],"difficult":[19],"to":[20,51,137,152],"separate":[21],"in":[22],"the":[23,62,73,130,138],"feature":[24],"domain.":[25],"Recently,":[26],"a":[27,32,38,78,108,153],"new":[28],"paradigm":[29],"based":[30,81],"Latent":[33],"Factor":[34,101],"Analysis":[35,102],"(LFA)":[36],"proposed":[37],"model":[39],"decomposition":[40],"into":[41],"usefull":[42],"components.":[45],"This":[46],"method":[47,80],"was":[48],"successfully":[49],"applied":[50],"speaker":[52],"language":[54],"recognition":[55],"tasks.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60],"study":[61],"use":[63],"LFA":[65],"for":[66],"video":[67,115],"genre":[68],"classification":[69,79,124],"by":[70,128],"using":[71,129],"only":[72],"audio":[74],"channel.":[75],"We":[76],"propose":[77],"short-term":[83],"cep-stral":[84],"Gaussian":[87,141],"Mixture":[88,142],"Models":[89],"(GMM)":[90],"or":[91],"Support":[92],"Vector":[93],"Machine":[94],"(SVM)":[95],"classifiers,":[96],"combined":[99],"with":[100,135],"(FA).":[103],"Experiments":[104],"conducted":[106],"corpus":[109],"composed":[110],"5":[112],"(musics,":[116],"commercials,":[117],"cartoons,":[118],"movies":[119],"news).":[121],"The":[122],"relative":[123],"error":[125],"reduction":[126],"obtained":[127],"best":[131],"factor":[132],"analysis":[133],"configuration":[134],"respect":[136],"baseline":[139],"system,":[140],"Model":[143,146],"Universal":[144],"Background":[145],"(GMM-UBM),":[147],"is":[148],"about":[149,158],"56%,":[150],"corresponding":[151],"correct":[154],"identification":[155],"rate":[156],"90%.":[159]},"counts_by_year":[{"year":2019,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
