{"id":"https://openalex.org/W3016107420","doi":"https://doi.org/10.1109/icassp40776.2020.9054628","title":"Polyphonic Sound Event Detection Using Transposed Convolutional Recurrent Neural Network","display_name":"Polyphonic Sound Event Detection Using Transposed Convolutional Recurrent Neural Network","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3016107420","doi":"https://doi.org/10.1109/icassp40776.2020.9054628","mag":"3016107420"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9054628","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054628","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5004760103","display_name":"Chandra Churh Chatterjee","orcid":null},"institutions":[{"id":"https://openalex.org/I4210098857","display_name":"Government of Himachal Pradesh","ror":"https://ror.org/013bmyp84","country_code":"IN","type":"government","lineage":["https://openalex.org/I4210098857"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Chandra Churh Chatterjee","raw_affiliation_strings":["Dept. of CSE, Jalpaiguri Government Engineering College, Jalpaiguri, India"],"affiliations":[{"raw_affiliation_string":"Dept. of CSE, Jalpaiguri Government Engineering College, Jalpaiguri, India","institution_ids":["https://openalex.org/I4210098857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053990884","display_name":"Manjunath Mulimani","orcid":"https://orcid.org/0000-0001-9927-1123"},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manjunath Mulimani","raw_affiliation_strings":["Dept. of CSE, Manipal Academy of Higher Education, Manipal, India"],"affiliations":[{"raw_affiliation_string":"Dept. of CSE, Manipal Academy of Higher Education, Manipal, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046622313","display_name":"Shashidhar G. Koolagudi","orcid":"https://orcid.org/0000-0002-6928-0237"},"institutions":[{"id":"https://openalex.org/I11880225","display_name":"National Institute of Technology Karnataka","ror":"https://ror.org/01hz4v948","country_code":"IN","type":"education","lineage":["https://openalex.org/I11880225"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shashidhar G. Koolagudi","raw_affiliation_strings":["Dept. of CSE, National Institute of Technology Karnataka, Surathkal, India"],"affiliations":[{"raw_affiliation_string":"Dept. of CSE, National Institute of Technology Karnataka, Surathkal, India","institution_ids":["https://openalex.org/I11880225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004760103"],"corresponding_institution_ids":["https://openalex.org/I4210098857"],"apc_list":null,"apc_paid":null,"fwci":0.9092,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.73219223,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"661","last_page":"665"},"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":0.9987000226974487,"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/T11349","display_name":"Music Technology and Sound Studies","score":0.9940999746322632,"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":0.9118930697441101},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7849683165550232},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.7623668909072876},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7075990438461304},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6894761323928833},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6863505244255066},{"id":"https://openalex.org/keywords/polyphony","display_name":"Polyphony","score":0.6570062637329102},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5507168769836426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.491219699382782},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4865188002586365},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3406520485877991},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.10907667875289917}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.9118930697441101},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7849683165550232},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.7623668909072876},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7075990438461304},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6894761323928833},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6863505244255066},{"id":"https://openalex.org/C128979739","wikidata":"https://www.wikidata.org/wiki/Q179465","display_name":"Polyphony","level":2,"score":0.6570062637329102},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5507168769836426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.491219699382782},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4865188002586365},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3406520485877991},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.10907667875289917},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9054628","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054628","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.41999998688697815,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W821549425","https://openalex.org/W1501987291","https://openalex.org/W1650531274","https://openalex.org/W2123843894","https://openalex.org/W2147917435","https://openalex.org/W2196961052","https://openalex.org/W2341412280","https://openalex.org/W2408239454","https://openalex.org/W2525167219","https://openalex.org/W2553581788","https://openalex.org/W2591013610","https://openalex.org/W2972581694","https://openalex.org/W6636898527","https://openalex.org/W6727553916"],"related_works":["https://openalex.org/W2411659965","https://openalex.org/W2387677326","https://openalex.org/W4200063482","https://openalex.org/W2357575019","https://openalex.org/W2370117122","https://openalex.org/W2530685530","https://openalex.org/W2360603947","https://openalex.org/W4375868962","https://openalex.org/W2371528275","https://openalex.org/W2964954556"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"propose":[4],"a":[5,24,38],"Transposed":[6,18],"Convolutional":[7],"Recurrent":[8,40],"Neural":[9,41],"Network":[10,42],"(TCRNN)":[11],"architecture":[12],"for":[13],"polyphonic":[14,84],"sound":[15,72,81,85],"event":[16,86],"recognition.":[17],"convolution":[19,26],"layer,":[20],"which":[21],"caries":[22],"out":[23],"regular":[25],"operation":[27],"but":[28],"reverts":[29],"the":[30,49,54,66,92],"spatial":[31],"transformation":[32],"and":[33,79,83],"it":[34],"is":[35,69],"combined":[36],"with":[37],"bidirectional":[39],"(RNN)":[43],"to":[44],"get":[45],"TCRNN.":[46],"Instead":[47],"of":[48,65,74],"traditional":[50],"mel":[51],"spectrogram":[52],"features,":[53],"proposed":[55,67,93],"methodology":[56],"incorporates":[57],"mel-IFgram":[58],"(Instantaneous":[59],"Frequency":[60],"spectrogram)":[61],"features.":[62],"The":[63],"performance":[64],"approach":[68,94],"evaluated":[70],"on":[71],"events":[73],"publicly":[75],"available":[76],"TUT-SED":[77],"2016":[78],"Joint":[80],"scene":[82],"recognition":[87],"datasets.":[88],"Results":[89],"show":[90],"that":[91],"outperforms":[95],"state-of-the-art":[96],"methods.":[97]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}