{"id":"https://openalex.org/W4387987019","doi":"https://doi.org/10.1109/taslp.2023.3325971","title":"CQT-Based Cepstral Features for Classification of Normal vs. Pathological Infant Cry","display_name":"CQT-Based Cepstral Features for Classification of Normal vs. Pathological Infant Cry","publication_year":2023,"publication_date":"2023-10-27","ids":{"openalex":"https://openalex.org/W4387987019","doi":"https://doi.org/10.1109/taslp.2023.3325971"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2023.3325971","doi":"https://doi.org/10.1109/taslp.2023.3325971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2023.3325971","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["ccf-b","cwts-core","dongbi-a","norway-2","poland-140","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5043002276","display_name":"Hemant A. Patil","orcid":"https://orcid.org/0000-0002-4068-2005","observed_orcids":["https://orcid.org/0000-0002-4068-2005","https://orcid.org/0009-0002-5765-2213"]},"institutions":[{"id":"https://openalex.org/I98389781","display_name":"Dhirubhai Ambani University","ror":"https://ror.org/02d5b7g69","country_code":"IN","type":"education","lineage":["https://openalex.org/I98389781"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Hemant A. Patil","raw_affiliation_strings":["ICT, Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, India","ICT, Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, Gujarat, India"],"raw_orcid":"https://orcid.org/0000-0002-4068-2005","affiliations":[{"raw_affiliation_string":"ICT, Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, India","institution_ids":["https://openalex.org/I98389781"]},{"raw_affiliation_string":"ICT, Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, Gujarat, India","institution_ids":["https://openalex.org/I98389781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071023061","display_name":"Aastha Kachhi","orcid":"https://orcid.org/0009-0002-2212-8606","observed_orcids":["https://orcid.org/0009-0002-2212-8606"]},"institutions":[{"id":"https://openalex.org/I98389781","display_name":"Dhirubhai Ambani University","ror":"https://ror.org/02d5b7g69","country_code":"IN","type":"education","lineage":["https://openalex.org/I98389781"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Aastha Kachhi","raw_affiliation_strings":["Speech Research Lab, Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, India"],"raw_orcid":"https://orcid.org/0009-0002-2212-8606","affiliations":[{"raw_affiliation_string":"Speech Research Lab, Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, India","institution_ids":["https://openalex.org/I98389781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079352542","display_name":"Ankur T. Patil","orcid":"https://orcid.org/0000-0002-5666-272X","observed_orcids":["https://orcid.org/0000-0002-5666-272X"]},"institutions":[{"id":"https://openalex.org/I98389781","display_name":"Dhirubhai Ambani University","ror":"https://ror.org/02d5b7g69","country_code":"IN","type":"education","lineage":["https://openalex.org/I98389781"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ankur T. Patil","raw_affiliation_strings":["ICT, Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, India","ICT, Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, Gujarat, India"],"raw_orcid":"https://orcid.org/0000-0002-5666-272X","affiliations":[{"raw_affiliation_string":"ICT, Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, India","institution_ids":["https://openalex.org/I98389781"]},{"raw_affiliation_string":"ICT, Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, Gujarat, India","institution_ids":["https://openalex.org/I98389781"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98389781"],"apc_list":{"value":2345,"currency":"USD","value_usd":2345},"apc_paid":null,"fwci":3.2743,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.91795703,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"32","issue":null,"first_page":"4713","last_page":"4726"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13289","display_name":"Infant Health and Development","score":0.9663000106811523,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T13289","display_name":"Infant Health and Development","score":0.9663000106811523,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.021900000050663948,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.001500000013038516,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/infant-cry-classification","display_name":"infant cry classification","score":0.9850000143051147},{"id":"https://openalex.org/keywords/constant-q-cepstral-coefficients","display_name":"constant Q cepstral coefficients","score":0.906000018119812},{"id":"https://openalex.org/keywords/constant-q-transform","display_name":"constant-Q transform","score":0.8149999976158142},{"id":"https://openalex.org/keywords/cepstral-features","display_name":"cepstral features","score":0.6819999814033508},{"id":"https://openalex.org/keywords/fundamental-frequency","display_name":"fundamental frequency","score":0.5709999799728394},{"id":"https://openalex.org/keywords/form-invariance","display_name":"form invariance","score":0.675000011920929},{"id":"https://openalex.org/keywords/gaussian-mixture-model","display_name":"Gaussian mixture model","score":0.6980000138282776},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.8289999961853027},{"id":"https://openalex.org/keywords/cross-database-evaluation","display_name":"cross-database evaluation","score":0.718999981880188},{"id":"https://openalex.org/keywords/feature-dimensionality","display_name":"feature dimensionality","score":0.4169999957084656},{"id":"https://openalex.org/keywords/spectral-resolution","display_name":"spectral resolution","score":0.4790000021457672}],"concepts":[{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.9220580458641052},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.6776442527770996},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.6576990485191345},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5977048873901367},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5704161524772644},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5682008266448975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5438989996910095},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4607679843902588},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45365893840789795},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4329238533973694},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.38359326124191284},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3390854001045227},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.13175830245018005},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taslp.2023.3325971","doi":"https://doi.org/10.1109/taslp.2023.3325971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2023.3325971","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["ccf-b","cwts-core","dongbi-a","norway-2","poland-140","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.4043000042438507}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320325255","display_name":"Ministry of Electronics and Information technology","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W20528612","https://openalex.org/W1510355813","https://openalex.org/W1557133539","https://openalex.org/W1586405805","https://openalex.org/W1838323663","https://openalex.org/W1976836279","https://openalex.org/W1979173241","https://openalex.org/W1994214279","https://openalex.org/W2008326590","https://openalex.org/W2010556851","https://openalex.org/W2020009023","https://openalex.org/W2023725399","https://openalex.org/W2070760745","https://openalex.org/W2072759936","https://openalex.org/W2076608692","https://openalex.org/W2082382711","https://openalex.org/W2102372511","https://openalex.org/W2105768320","https://openalex.org/W2116559130","https://openalex.org/W2129910485","https://openalex.org/W2136472617","https://openalex.org/W2148154194","https://openalex.org/W2152575748","https://openalex.org/W2155214087","https://openalex.org/W2158698691","https://openalex.org/W2161278885","https://openalex.org/W2171044784","https://openalex.org/W2259135914","https://openalex.org/W2295634712","https://openalex.org/W2303197844","https://openalex.org/W2399892072","https://openalex.org/W2401484345","https://openalex.org/W2490662969","https://openalex.org/W2504507112","https://openalex.org/W2522286455","https://openalex.org/W2590129515","https://openalex.org/W2769035248","https://openalex.org/W2936802426","https://openalex.org/W2954380638","https://openalex.org/W2981822782","https://openalex.org/W3016080232","https://openalex.org/W3088864046","https://openalex.org/W3090558582","https://openalex.org/W3092674089","https://openalex.org/W3134611008","https://openalex.org/W3174716293","https://openalex.org/W3206579217","https://openalex.org/W3207911573","https://openalex.org/W4225317694","https://openalex.org/W4301423176","https://openalex.org/W4302067267","https://openalex.org/W4312097369","https://openalex.org/W4312867479","https://openalex.org/W4324284894"],"related_works":["https://openalex.org/W4225317694","https://openalex.org/W4388878646","https://openalex.org/W4313182769","https://openalex.org/W4319586325","https://openalex.org/W4321843595","https://openalex.org/W4388854299","https://openalex.org/W2093207235","https://openalex.org/W2804807665","https://openalex.org/W2147348451","https://openalex.org/W4285271071"],"abstract_inverted_index":{"Infant":[0],"cry":[1,12,120],"classification":[2,76,199],"is":[3,154,279],"an":[4,263],"important":[5],"area":[6],"of":[7,48,126,148,201,221,225,241,247,266,277,301,322,328,340],"research":[8],"that":[9,190],"involves":[10],"analyzing":[11],"to":[13,72,79,87,103],"detect":[14],"and":[15,35,66,111,142,164,182,203,209,244,258,320],"classify":[16],"between":[17],"normalvs.":[18],"pathological":[19],"cries.":[20],"However,":[21],"signal":[22,282],"processing":[23],"based":[24],"state-of-the-art":[25,157],"feature":[26,69,129,152,166,249,272,310],"sets,":[27],"such":[28,315],"as":[29],"Short-Time":[30],"Fourier":[31],"Transform":[32],"(STFT)":[33],"representations":[34],"Mel":[36],"Frequency":[37,160],"Cepstral":[38,100,161,165],"Coefficients":[39,101,162],"(MFCC),":[40],"have":[41,133],"been":[42,134],"earlier":[43],"reported":[44],"for":[45,118,325],"this":[46,84,137,215,235,252,333],"task.Quasi-periodicsampling":[47],"the":[49,64,80,94,106,127,149,206,219,222,226,229,239,248,255,269,275,299,302,308,326,329,336,343,347],"vocal":[50],"tract":[51],"spectrum":[52],"by":[53],"high":[54],"pitch":[55],"source":[56],"harmonics":[57,113],"results":[58,192,339],"in":[59,63,93,136],"poor":[60],"spectral":[61],"resolution":[62],"STFT":[65],"hence,":[67],"these":[68],"sets":[70,311],"fail":[71],"produce":[73],"a":[74,123],"satisfactory":[75],"performance.":[77],"Contrary":[78],"linearly-spaced":[81],"frequency":[82,90,109],"bins,":[83],"study":[85,188,236,253,334],"proposes":[86],"use":[88],"geometrically-spaced":[89],"bins":[91],"employed":[92],"CQT-based":[95],"features,":[96],"namely,":[97,139,177],"Constant":[98],"Q":[99],"(CQCC)":[102],"systematically":[104],"emphasize":[105],"required":[107],"fundamental":[108],"(F0)":[110],"its":[112],"(kF0,":[114],"k":[115],"\u220a":[116],"Z)":[117],"infant":[119],"classification.":[121],"For":[122],"comprehensive":[124],"evaluation":[125],"proposed":[128,150,270,303],"set,":[130],"two":[131,174],"datasets":[132],"considered":[135],"work,":[138],"Baby":[140,207,348],"Chilanto":[141,208,349],"In-House":[143,210],"DA-IICT":[144,211],"datasets.":[145,297],"The":[146],"performance":[147,300],"CQCC":[151,271,278,304,341],"set":[153],"compared":[155,306],"against":[156],"MFCC,":[158],"Linear":[159],"(LFCC),":[163],"sets.":[167],"Experiments":[168],"were":[169,193],"performed":[170],"using10-fold":[171],"cross-validation":[172],"on":[173,205,268,295,346],"traditional":[175,230],"classifiers,":[176],"Gaussian":[178],"Mixture":[179],"Model":[180],"(GMM)":[181],"Support":[183],"Vector":[184],"Machine":[185],"(SVM).":[186],"Our":[187],"finds":[189],"better":[191],"obtained":[194,338],"using":[195,312],"CQCC-GMM":[196],"architecture":[197],"with":[198,262,285,307,342],"accuracies":[200],"99.8%":[202],"98.24%":[204],"datasets,":[212],"respectively.":[213],"Further,":[214],"work":[216],"also":[217,237],"illustrates":[218],"effectiveness":[220],"form-invariance":[223],"property":[224],"CQT":[227],"over":[228],"narrowband":[231],"STFTbased":[232],"spectrogram.":[233],"Furthermore,":[234,251],"presents":[238,254],"effect":[240],"parameter":[242,245],"tuning":[243],"dimension":[246],"vector.":[250],"first-ever":[256],"cross-database":[257],"combined":[259],"dataset":[260],"scenarios":[261],"overall":[264],"improvement":[265],"1.59%":[267],"set.":[273],"Additionally,":[274],"robustness":[276],"evaluated":[280],"under":[281],"degradation":[283],"conditions":[284],"additive":[286],"babble":[287],"noise":[288],"having":[289],"various":[290],"Signal-to-Noise":[291],"Ratio":[292],"(SNR)":[293],"levels":[294],"both":[296],"Next,":[298],"was":[305],"other":[309],"statistical":[313],"measures,":[314],"asF1-score,":[316],"J-statistics,":[317],"violin":[318],"plots,":[319],"analysis":[321],"latency":[323],"period":[324],"deployment":[327],"practical":[330],"system.":[331],"Finally,":[332],"compares":[335],"best":[337],"existing":[344],"studies":[345],"dataset.":[350]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2023-10-28T00:00:00"}