{"id":"https://openalex.org/W6959693792","doi":"https://doi.org/10.1109/tencon61640.2024.10902912","title":"Quartered Chirp Spectral Envelope for Whispered vs Normal Speech Classification","display_name":"Quartered Chirp Spectral Envelope for Whispered vs Normal Speech Classification","publication_year":2024,"publication_date":"2024-12-01","ids":{"openalex":"https://openalex.org/W6959693792","doi":"https://doi.org/10.1109/tencon61640.2024.10902912"},"language":"en","primary_location":{"id":"doi:10.1109/tencon61640.2024.10902912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon61640.2024.10902912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON)","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":null,"display_name":"S. Johanan Joysingh","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"S. Johanan Joysingh","raw_affiliation_strings":["Vellore Institute of Technology,Chennai,India"],"affiliations":[{"raw_affiliation_string":"Vellore Institute of Technology,Chennai,India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"middle","author":{"id":null,"display_name":"P. Vijayalakshmi","orcid":null},"institutions":[{"id":"https://openalex.org/I916357946","display_name":"Sri Sivasubramaniya Nadar College of Engineering","ror":"https://ror.org/054psm803","country_code":null,"type":"education","lineage":["https://openalex.org/I916357946"]},{"id":"https://openalex.org/I20107917","display_name":"Sri Ramachandra Institute of Higher Education and Research","ror":"https://ror.org/0108gdg43","country_code":"IN","type":"education","lineage":["https://openalex.org/I20107917"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"P. Vijayalakshmi","raw_affiliation_strings":["Sri Sivasubramaniya Nadar College of Engineering,Chennai,India"],"affiliations":[{"raw_affiliation_string":"Sri Sivasubramaniya Nadar College of Engineering,Chennai,India","institution_ids":["https://openalex.org/I916357946","https://openalex.org/I20107917"]}]},{"author_position":"last","author":{"id":null,"display_name":"T. Nagarajan","orcid":null},"institutions":[{"id":"https://openalex.org/I26604189","display_name":"Shiv Nadar University","ror":"https://ror.org/05aqahr97","country_code":"IN","type":"education","lineage":["https://openalex.org/I26604189"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"T. Nagarajan","raw_affiliation_strings":["Shiv Nadar University,Chennai,India"],"affiliations":[{"raw_affiliation_string":"Shiv Nadar University,Chennai,India","institution_ids":["https://openalex.org/I26604189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I876193797"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.50568365,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1364","last_page":"1367"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11745","display_name":"Potato Plant Research","score":0.14309999346733093,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11745","display_name":"Potato Plant Research","score":0.14309999346733093,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11771","display_name":"Plant Pathogens and Resistance","score":0.13259999454021454,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10012","display_name":"Genetic diversity and population structure","score":0.04670000076293945,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/chirp","display_name":"Chirp","score":0.6868000030517578},{"id":"https://openalex.org/keywords/spectral-envelope","display_name":"Spectral envelope","score":0.6399000287055969},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5101000070571899},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.476500004529953},{"id":"https://openalex.org/keywords/envelope","display_name":"Envelope (radar)","score":0.4025000035762787},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3720000088214874},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.357699990272522}],"concepts":[{"id":"https://openalex.org/C132794960","wikidata":"https://www.wikidata.org/wiki/Q27304","display_name":"Chirp","level":3,"score":0.6868000030517578},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6597999930381775},{"id":"https://openalex.org/C54926389","wikidata":"https://www.wikidata.org/wiki/Q7575188","display_name":"Spectral envelope","level":2,"score":0.6399000287055969},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5101000070571899},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.476500004529953},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45210000872612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40529999136924744},{"id":"https://openalex.org/C65155139","wikidata":"https://www.wikidata.org/wiki/Q5380912","display_name":"Envelope (radar)","level":3,"score":0.4025000035762787},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39739999175071716},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3720000088214874},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.357699990272522},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.33090001344680786},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.3262999951839447},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.28769999742507935},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.25870001316070557},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.25220000743865967}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon61640.2024.10902912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon61640.2024.10902912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W37326695","https://openalex.org/W41355022","https://openalex.org/W2103030298","https://openalex.org/W2889933531","https://openalex.org/W2972924908","https://openalex.org/W3100777112","https://openalex.org/W3117655743","https://openalex.org/W4205976327","https://openalex.org/W4312164130","https://openalex.org/W4391988196","https://openalex.org/W6636560676","https://openalex.org/W6684352069","https://openalex.org/W6773478093","https://openalex.org/W7008777630"],"related_works":[],"abstract_inverted_index":{"Whispered":[0],"speech":[1,18,23,30,43],"as":[2],"an":[3],"acceptable":[4],"form":[5],"of":[6,17,26,36,47,50,69,141,147],"human-computer":[7],"interaction":[8],"is":[9,116],"gaining":[10],"traction.":[11],"Systems":[12],"that":[13,125],"address":[14],"multiple":[15],"modes":[16],"require":[19],"a":[20,58,67,95,119],"robust":[21],"front-end":[22],"clasifier.":[24],"Performance":[25],"whispered":[27,51,80],"vs":[28],"normal":[29,42,82],"classification":[31],"drops":[32],"in":[33,129,144],"the":[34,48,62,70,74,99,111,127,130,139,142,145],"presence":[35,146],"additive":[37],"white":[38,148],"Gaussian":[39],"noise,":[40],"since":[41],"takes":[44],"on":[45,118],"some":[46],"characteristics":[49],"speech.":[52,83],"In":[53],"this":[54],"work,":[55],"we":[56],"propose":[57],"new":[59],"feature":[60,115],"named":[61],"quartered":[63,75,100],"chirp":[64,71,85],"spectral":[65,76,101,131],"envelope,":[66,77],"combination":[68],"spectrum":[72,86],"and":[73,81,98],"to":[78,90,106],"classify":[79],"The":[84,114,133],"can":[87],"be":[88],"fine-tuned":[89],"obtain":[91],"customized":[92],"features":[93],"for":[94,110],"given":[96],"task,":[97],"envelope":[102],"has":[103],"been":[104],"proven":[105],"work":[107],"especially":[108],"well":[109],"current":[112],"task.":[113],"trained":[117],"one":[120],"dimensional":[121],"convolutional":[122],"neural":[123],"network,":[124],"captures":[126],"trends":[128],"envelope.":[132],"proposed":[134],"system":[135],"performs":[136],"better":[137],"than":[138],"state":[140],"art,":[143],"noise.":[149]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
