{"id":"https://openalex.org/W2162916741","doi":"https://doi.org/10.1109/cbmi.2014.6849814","title":"A robust audio fingerprinting method for content-based copy detection","display_name":"A robust audio fingerprinting method for content-based copy detection","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2162916741","doi":"https://doi.org/10.1109/cbmi.2014.6849814","mag":"2162916741"},"language":"en","primary_location":{"id":"doi:10.1109/cbmi.2014.6849814","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbmi.2014.6849814","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 12th International Workshop on Content-Based Multimedia Indexing (CBMI)","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/A5031518818","display_name":"Chahid Ouali","orcid":null},"institutions":[{"id":"https://openalex.org/I9736820","display_name":"\u00c9cole de Technologie Sup\u00e9rieure","ror":"https://ror.org/0020snb74","country_code":"CA","type":"education","lineage":["https://openalex.org/I49663120","https://openalex.org/I9736820"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Chahid Ouali","raw_affiliation_strings":["\u00c9TS (\u00c9cole de Technologie Sup\u00e9rieure Montreal, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\u00c9TS (\u00c9cole de Technologie Sup\u00e9rieure Montreal, Canada","institution_ids":["https://openalex.org/I9736820"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034083532","display_name":"Pierre Dumouchel","orcid":"https://orcid.org/0000-0001-5584-4428"},"institutions":[{"id":"https://openalex.org/I9736820","display_name":"\u00c9cole de Technologie Sup\u00e9rieure","ror":"https://ror.org/0020snb74","country_code":"CA","type":"education","lineage":["https://openalex.org/I49663120","https://openalex.org/I9736820"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Pierre Dumouchel","raw_affiliation_strings":["Ecole de technologie superieure, Montreal, QC, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ecole de technologie superieure, Montreal, QC, CA","institution_ids":["https://openalex.org/I9736820"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114009216","display_name":"Vishwa Gupta","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111842","display_name":"Computer Research Institute of Montr\u00e9al","ror":"https://ror.org/0279d5115","country_code":"CA","type":"nonprofit","lineage":["https://openalex.org/I4210111842"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Vishwa Gupta","raw_affiliation_strings":["CRIM (Computer Research Institute of Montreal), Montreal, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CRIM (Computer Research Institute of Montreal), Montreal, Canada","institution_ids":["https://openalex.org/I4210111842"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5031518818"],"corresponding_institution_ids":["https://openalex.org/I9736820"],"apc_list":null,"apc_paid":null,"fwci":3.8312,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.94414301,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9973000288009644,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9937000274658203,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.7969554662704468},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7658985257148743},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7380924224853516},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5627961158752441},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5558167099952698},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4683598577976227},{"id":"https://openalex.org/keywords/audio-signal","display_name":"Audio signal","score":0.4627869427204132},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4343586564064026},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.40132710337638855},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.3398362100124359},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2597259283065796},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.178150475025177}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.7969554662704468},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7658985257148743},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7380924224853516},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5627961158752441},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5558167099952698},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4683598577976227},{"id":"https://openalex.org/C64922751","wikidata":"https://www.wikidata.org/wiki/Q4650799","display_name":"Audio signal","level":3,"score":0.4627869427204132},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4343586564064026},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.40132710337638855},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.3398362100124359},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2597259283065796},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.178150475025177},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cbmi.2014.6849814","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbmi.2014.6849814","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 12th International Workshop on Content-Based Multimedia Indexing (CBMI)","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":20,"referenced_works":["https://openalex.org/W83334756","https://openalex.org/W122994913","https://openalex.org/W166806076","https://openalex.org/W1498631286","https://openalex.org/W1510532633","https://openalex.org/W1968090956","https://openalex.org/W1974418584","https://openalex.org/W2023854218","https://openalex.org/W2032913923","https://openalex.org/W2062903088","https://openalex.org/W2080470053","https://openalex.org/W2096598726","https://openalex.org/W2097387583","https://openalex.org/W2104160358","https://openalex.org/W2161647295","https://openalex.org/W2527334262","https://openalex.org/W3021680550","https://openalex.org/W3021908862","https://openalex.org/W6604987197","https://openalex.org/W6606722388"],"related_works":["https://openalex.org/W2530685530","https://openalex.org/W4375868962","https://openalex.org/W2011227383","https://openalex.org/W2088854863","https://openalex.org/W3179495260","https://openalex.org/W1976719989","https://openalex.org/W3127543252","https://openalex.org/W4360764600","https://openalex.org/W2109142991","https://openalex.org/W2350061705"],"abstract_inverted_index":{"This":[0,82],"paper":[1],"presents":[2],"a":[3,13,45,69,79,96,113,154],"novel":[4],"audio":[5,16,23,41,145,156,188],"fingerprinting":[6],"method":[7,125,152,167],"that":[8,165],"is":[9,19,29,146],"highly":[10],"robust":[11],"to":[12,55,78,153],"variety":[14],"of":[15,35,39,51,63,85,90,92,139,161,171],"distortions.":[17],"It":[18],"based":[20,47,117],"on":[21,48,118,126],"unconventional":[22],"fingerprints":[24,141],"generation":[25],"scheme.":[26],"The":[27],"robustness":[28],"achieved":[30],"by":[31,43,185],"generating":[32],"different":[33],"versions":[34],"the":[36,40,49,52,93,137,144,150],"spectrogram":[37,66],"matrix":[38,67],"signal":[42],"using":[44],"threshold":[46],"average":[50],"spectral":[53],"values":[54],"prune":[56],"this":[57,64,119,124,162],"matrix.":[58],"We":[59,122,148],"transform":[60],"each":[61,105],"version":[62],"pruned":[65],"into":[68,107],"2-D":[70,74],"binary":[71],"image.":[72,98],"Multiple":[73],"images":[75,94],"suppress":[76],"noise":[77,86],"varying":[80,83],"degree.":[81],"degree":[84],"suppression":[87],"improves":[88],"likelihood":[89],"one":[91],"matching":[95],"reference":[97],"To":[99],"speed":[100],"up":[101],"matching,":[102],"we":[103],"convert":[104],"image":[106],"an":[108,169],"n-dimensional":[109,120],"vector,":[110],"and":[111,176,191],"perform":[112],"nearest":[114],"neighbor":[115],"search":[116],"vector.":[121],"test":[123],"TRECVID":[127],"2010":[128],"content-based":[129],"copy":[130,157],"detection":[131,158,180],"evaluation":[132],"dataset.":[133],"Experimental":[134],"results":[135],"show":[136,164],"effectiveness":[138],"such":[140],"even":[142],"when":[143],"distorted.":[147],"compare":[149],"proposed":[151],"state-of-the-art":[155],"system.":[159],"Results":[160],"comparison":[163],"our":[166],"achieves":[168],"improvement":[170],"22%":[172],"in":[173],"localization":[174],"accuracy,":[175],"lowers":[177],"minimal":[178],"normalized":[179],"cost":[181],"rate":[182],"(min":[183],"NDCR)":[184],"half":[186],"for":[187],"transformations":[189],"T1":[190],"T2.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":7}],"updated_date":"2026-05-04T08:30:34.212998","created_date":"2025-10-10T00:00:00"}
