{"id":"https://openalex.org/W2088531228","doi":"https://doi.org/10.1109/icassp.2013.6637693","title":"Traffic density state estimation based on acoustic fusion","display_name":"Traffic density state estimation based on acoustic fusion","publication_year":2013,"publication_date":"2013-05-01","ids":{"openalex":"https://openalex.org/W2088531228","doi":"https://doi.org/10.1109/icassp.2013.6637693","mag":"2088531228"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2013.6637693","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6637693","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","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/A5019937451","display_name":"Vikas Joshi","orcid":"https://orcid.org/0000-0003-4467-3621"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Vikas Joshi","raw_affiliation_strings":["IBM India Research Laboratory, New Delhi, India","IBM, India Research Lab., New Delhi, India#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM India Research Laboratory, New Delhi, India","institution_ids":["https://openalex.org/I4210103279"]},{"raw_affiliation_string":"IBM, India Research Lab., New Delhi, India#TAB#","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014550071","display_name":"Nithya Rajamani","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Nithya Rajamani","raw_affiliation_strings":["IBM India Research Laboratory, New Delhi, India","IBM, India Research Lab., New Delhi, India#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM India Research Laboratory, New Delhi, India","institution_ids":["https://openalex.org/I4210103279"]},{"raw_affiliation_string":"IBM, India Research Lab., New Delhi, India#TAB#","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001222774","display_name":"Naveen Prathapaneni","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Naveen Prathapaneni","raw_affiliation_strings":["IBM India Research Laboratory, New Delhi, India","IBM, India Research Lab., New Delhi, India#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM India Research Laboratory, New Delhi, India","institution_ids":["https://openalex.org/I4210103279"]},{"raw_affiliation_string":"IBM, India Research Lab., New Delhi, India#TAB#","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110205806","display_name":"L. V. Subramaniam","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"L. V. Subramaniam","raw_affiliation_strings":["IBM India Research Laboratory, New Delhi, India","IBM, India Research Lab., New Delhi, India#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM India Research Laboratory, New Delhi, India","institution_ids":["https://openalex.org/I4210103279"]},{"raw_affiliation_string":"IBM, India Research Lab., New Delhi, India#TAB#","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.15433025,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"s5","issue":null,"first_page":"478","last_page":"482"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9993000030517578,"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":0.9993000030517578,"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/T10860","display_name":"Speech and Audio Processing","score":0.9970999956130981,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.8405352830886841},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7163457274436951},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7154473066329956},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6373859643936157},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5241313576698303},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46768835186958313},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.445919007062912},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.42857295274734497},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3675309419631958},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.29101020097732544}],"concepts":[{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.8405352830886841},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7163457274436951},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7154473066329956},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6373859643936157},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5241313576698303},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46768835186958313},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.445919007062912},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.42857295274734497},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3675309419631958},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.29101020097732544}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2013.6637693","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6637693","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1530111162","https://openalex.org/W2024415913","https://openalex.org/W2093685172","https://openalex.org/W2125826911","https://openalex.org/W2130251794","https://openalex.org/W2134723767","https://openalex.org/W2144169341","https://openalex.org/W2154500405","https://openalex.org/W2163404190","https://openalex.org/W2167707355","https://openalex.org/W3216566650","https://openalex.org/W6679949672","https://openalex.org/W6684250182","https://openalex.org/W6804055087"],"related_works":["https://openalex.org/W2990982991","https://openalex.org/W2736574136","https://openalex.org/W2038216521","https://openalex.org/W1487808658","https://openalex.org/W4399693842","https://openalex.org/W2399955410","https://openalex.org/W3126677997","https://openalex.org/W2565286512","https://openalex.org/W2097377227","https://openalex.org/W2933782699"],"abstract_inverted_index":{"In":[0,16],"this":[1],"paper,":[2],"we":[3,18],"propose":[4,91],"an":[5,85],"acoustic":[6],"fusion":[7,87],"based":[8,27,39,42,70],"approach":[9],"to":[10,92,98],"classify":[11],"the":[12,20,31,48,64,101],"traffic":[13,53],"density":[14],"states.":[15],"particular,":[17],"combine":[19],"information":[21,69,96],"from":[22,73],"mel-frequency":[23],"cepstral":[24],"coefficients":[25],"(MFCC)":[26],"classifier,":[28],"which":[29],"models":[30],"cumulative":[32],"road":[33],"side":[34],"signal":[35],"and":[36,58,75],"honk":[37,49,68,76,95],"event":[38],"classifier.":[40,71],"Honk":[41],"classifier":[43,77],"is":[44],"obtained":[45],"by":[46],"modeling":[47],"statistics":[50],"for":[51],"each":[52],"class,":[54],"viz.,":[55],"Jam,":[56],"Medium":[57],"Free.":[59],"We":[60,89],"study":[61],"in":[62,81],"detail":[63],"discriminative":[65],"capabilities":[66],"of":[67,112],"Decisions":[72],"MFCC":[74],"are":[78],"then":[79],"combined":[80],"probabilistic":[82],"framework":[83],"with":[84,110],"appropriate":[86],"strategy.":[88],"also":[90],"use":[93],"prior":[94],"in-order":[97],"further":[99],"improve":[100],"classification":[102],"results.":[103],"Classification":[104],"results":[105],"show":[106],"good":[107],"performance":[108],"even":[109],"10s":[111],"audio":[113],"data.":[114]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}