{"id":"https://openalex.org/W2903498744","doi":"https://doi.org/10.23919/eusipco.2018.8553131","title":"Acoustic Event Classification Using Multi-Resolution HMM","display_name":"Acoustic Event Classification Using Multi-Resolution HMM","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2903498744","doi":"https://doi.org/10.23919/eusipco.2018.8553131","mag":"2903498744"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2018.8553131","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553131","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","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/A5013350630","display_name":"Paul M. Baggenstoss","orcid":"https://orcid.org/0000-0002-3739-6104"},"institutions":[{"id":"https://openalex.org/I4210166245","display_name":"Fraunhofer Institute for Communication, Information Processing and Ergonomics","ror":"https://ror.org/05nn0gw40","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210166245","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Paul M. Baggenstoss","raw_affiliation_strings":["Fraunhofer FKIE, Fraunhoferstrasse 20, Wachtberg, 53343, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer FKIE, Fraunhoferstrasse 20, Wachtberg, 53343, Germany","institution_ids":["https://openalex.org/I4210166245"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5013350630"],"corresponding_institution_ids":["https://openalex.org/I4210166245"],"apc_list":null,"apc_paid":null,"fwci":0.3303,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.5848969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"972","last_page":"976"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":1.0,"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":1.0,"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":0.9986000061035156,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9926999807357788,"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/hidden-markov-model","display_name":"Hidden Markov model","score":0.9203695058822632},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7798495292663574},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7155786752700806},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6864626407623291},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.679080605506897},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.568187952041626},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5374247431755066},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5113450884819031},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4565051198005676}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.9203695058822632},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7798495292663574},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7155786752700806},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6864626407623291},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.679080605506897},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.568187952041626},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5374247431755066},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5113450884819031},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4565051198005676}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.23919/eusipco.2018.8553131","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553131","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},{"id":"pmh:oai:fraunhofer.de:N-524017","is_oa":false,"landing_page_url":"http://publica.fraunhofer.de/documents/N-524017.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer FKIE","raw_type":"Conference Paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/402791","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/402791","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1559359311","https://openalex.org/W1597985425","https://openalex.org/W1819491323","https://openalex.org/W1970578576","https://openalex.org/W1970732261","https://openalex.org/W1972567154","https://openalex.org/W1987011838","https://openalex.org/W2009504845","https://openalex.org/W2018490621","https://openalex.org/W2045871908","https://openalex.org/W2046972719","https://openalex.org/W2054658115","https://openalex.org/W2064543148","https://openalex.org/W2070004089","https://openalex.org/W2096044236","https://openalex.org/W2109301048","https://openalex.org/W2125838338","https://openalex.org/W2131712117","https://openalex.org/W2171966314","https://openalex.org/W2174228052","https://openalex.org/W2215930354","https://openalex.org/W2221333906","https://openalex.org/W2552850818","https://openalex.org/W2555708919","https://openalex.org/W2581803003","https://openalex.org/W2754744771","https://openalex.org/W2963922351","https://openalex.org/W4211150175","https://openalex.org/W4285719527","https://openalex.org/W6643326691","https://openalex.org/W6674653747","https://openalex.org/W6987678730"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2167155152","https://openalex.org/W1974738623","https://openalex.org/W1487808658"],"abstract_inverted_index":{"Real-world":[0],"acoustic":[1,96],"events":[2],"span":[3],"a":[4,20,30,37,73,81,116],"wide":[5,74],"range":[6,75],"of":[7,51,76,83,104,134],"time":[8,40],"and":[9,33,41,78,127,141],"frequency":[10,42],"resolutions,":[11],"from":[12],"short":[13],"clicks":[14],"to":[15,102,138],"longer":[16],"tonals.":[17],"This":[18],"is":[19,48,88,149],"challenge":[21],"for":[22],"the":[23,52,91,105,119,122,147],"hidden":[24],"Markov":[25],"model":[26],"(HMM),":[27],"which":[28],"uses":[29],"fixed":[31],"segmentation":[32],"feature":[34,84],"extraction,":[35],"forcing":[36],"compromise":[38],"between":[39],"resolution.":[43],"The":[44],"multiresolution":[45],"HMM":[46,53],"(MR-HMM)":[47],"an":[49,58,66,95],"extension":[50],"that":[54,90,154],"assumes":[55],"not":[56],"only":[57],"underlying":[59,67,123],"(hidden)":[60],"random":[61,68],"state":[62,103],"sequence,":[63],"but":[64],"also":[65],"segmentation,":[69],"with":[70,151],"segments":[71],"spanning":[72],"sizes":[77],"processed":[79],"using":[80],"variety":[82],"extraction":[85],"methods.":[86],"It":[87],"shown":[89],"MR-HMM":[92,120,148],"alone,":[93],"as":[94,115],"event":[97],"classifier,":[98,118],"has":[99],"performance":[100],"comparable":[101],"art":[106],"discriminative":[107],"classifiers":[108],"on":[109],"three":[110],"open":[111],"data":[112,124],"sets.":[113],"However,":[114],"generative":[117],"models":[121,137],"generation":[125],"process":[126],"can":[128],"generate":[129],"synthetic":[130],"data,":[131],"allowing":[132],"weaknesses":[133],"individual":[135],"class":[136],"be":[139],"discovered":[140],"corrected.":[142],"To":[143],"demonstrate":[144],"this":[145],"point,":[146],"combined":[150],"auxiliary":[152],"features":[153],"capture":[155],"temporal":[156],"information,":[157],"resulting":[158],"in":[159],"significantly":[160],"improved":[161],"performance.":[162]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}