{"id":"https://openalex.org/W2789962914","doi":"https://doi.org/10.1109/cisp-bmei.2017.8302139","title":"A denosing method of frequency spectrum for recognition of dashboard sounds","display_name":"A denosing method of frequency spectrum for recognition of dashboard sounds","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2789962914","doi":"https://doi.org/10.1109/cisp-bmei.2017.8302139","mag":"2789962914"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2017.8302139","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2017.8302139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5100339743","display_name":"Pengfei Li","orcid":"https://orcid.org/0000-0002-1484-0698"},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pengfei Li","raw_affiliation_strings":["College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian, China"],"affiliations":[{"raw_affiliation_string":"College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002112471","display_name":"Qingxiang Wu","orcid":"https://orcid.org/0000-0003-4262-8210"},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingxiang Wu","raw_affiliation_strings":["College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian, China"],"affiliations":[{"raw_affiliation_string":"College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102919303","display_name":"Caiyun Wu","orcid":"https://orcid.org/0009-0000-9069-287X"},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Caiyun Wu","raw_affiliation_strings":["College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian, China"],"affiliations":[{"raw_affiliation_string":"College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042736472","display_name":"Caiyou Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Caiyou Yuan","raw_affiliation_strings":["College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian, China"],"affiliations":[{"raw_affiliation_string":"College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I111753288"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100339743"],"corresponding_institution_ids":["https://openalex.org/I111753288"],"apc_list":null,"apc_paid":null,"fwci":0.1849,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.50507141,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech 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/T10860","display_name":"Speech 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/T12759","display_name":"Vehicle Noise and Vibration Control","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/computer-science","display_name":"Computer science","score":0.6624088287353516},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6354979276657104},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6346892714500427},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5687138438224792},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5483810901641846},{"id":"https://openalex.org/keywords/sound","display_name":"Sound (geography)","score":0.5205327272415161},{"id":"https://openalex.org/keywords/audio-signal","display_name":"Audio signal","score":0.4733840525150299},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45930609107017517},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.45842185616493225},{"id":"https://openalex.org/keywords/dashboard","display_name":"Dashboard","score":0.45014551281929016},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.4338081181049347},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4276025891304016},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.419564813375473},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.32422998547554016},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2637943923473358},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.07834476232528687}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6624088287353516},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6354979276657104},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6346892714500427},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5687138438224792},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5483810901641846},{"id":"https://openalex.org/C203718221","wikidata":"https://www.wikidata.org/wiki/Q491713","display_name":"Sound (geography)","level":2,"score":0.5205327272415161},{"id":"https://openalex.org/C64922751","wikidata":"https://www.wikidata.org/wiki/Q4650799","display_name":"Audio signal","level":3,"score":0.4733840525150299},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45930609107017517},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.45842185616493225},{"id":"https://openalex.org/C33499554","wikidata":"https://www.wikidata.org/wiki/Q1417134","display_name":"Dashboard","level":2,"score":0.45014551281929016},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.4338081181049347},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4276025891304016},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.419564813375473},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.32422998547554016},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2637943923473358},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.07834476232528687},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei.2017.8302139","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2017.8302139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1589717461","https://openalex.org/W2023244931","https://openalex.org/W2025760455","https://openalex.org/W2026785701","https://openalex.org/W2111209327","https://openalex.org/W2111793199","https://openalex.org/W2151662931","https://openalex.org/W2153762815","https://openalex.org/W2256507023","https://openalex.org/W2586419604","https://openalex.org/W6656478433"],"related_works":["https://openalex.org/W2607236244","https://openalex.org/W2382083831","https://openalex.org/W4239369595","https://openalex.org/W2169792944","https://openalex.org/W3048913176","https://openalex.org/W4386891374","https://openalex.org/W4292603292","https://openalex.org/W2048767857","https://openalex.org/W2808637346","https://openalex.org/W2947439131"],"abstract_inverted_index":{"In":[0],"this":[1,21,162],"article":[2],"a":[3,101],"frequency":[4],"spectrum-based":[5],"approach":[6,141],"is":[7,23,55,83,93,98,116,123,164],"proposed":[8,144],"to":[9,24,125,131,145,166],"extract":[10],"features":[11],"and":[12,67,91,105,120,151,170],"identify":[13,25],"warning":[14,27],"tones":[15,28],"from":[16,30,58],"dashboard.":[17],"The":[18,80,128],"purpose":[19],"of":[20,46,50,65,73,157],"paper":[22],"the":[26,31,47,53,59,63,70,86,96,111,121,136,148,153,158],"emitted":[29],"dashboard,":[32],"such":[33],"as":[34,62,78,110],"turn":[35],"signal":[36],"lights,":[37,42],"unmanned":[38],"seat":[39],"belts,":[40],"position":[41],"etc.":[43],"After":[44],"analysis":[45],"spectral":[48,60,149,155],"characteristics":[49,61,156],"sound":[51,82,104,107,119],"signals,":[52],"information":[54],"extracted":[56],"directly":[57],"basis":[64],"classification":[66],"identification.":[68],"Firstly,":[69],"standard":[71,159],"voices":[72],"different":[74],"instruments":[75],"are":[76,108],"collected":[77],"templates.":[79],"test":[81,103],"compared":[84],"with":[85],"template":[87,106],"sounds":[88],"when":[89],"testing,":[90],"similarity":[92,97],"calculated.":[94],"When":[95],"higher":[99],"than":[100],"threshold,":[102],"regarded":[109],"same":[112],"voice.":[113],"Otherwise":[114],"that":[115],"not":[117],"qualified":[118],"meter":[122],"considered":[124],"be":[126],"defective.":[127],"usual":[129],"way":[130],"remove":[132],"noise":[133],"was":[134],"in":[135,147],"time":[137],"domain.":[138],"A":[139],"new":[140],"has":[142,171],"been":[143],"denoise":[146],"space":[150],"obtain":[152],"efficiently":[154],"sounds.":[160],"Finally":[161],"method":[163],"applied":[165],"dashboard":[167],"voice":[168],"recognition":[169],"achieved":[172],"good":[173],"results.":[174]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}