{"id":"https://openalex.org/W2766609943","doi":"https://doi.org/10.1109/ncc.2017.8077043","title":"Investigative study of various activation functions for speech recognition","display_name":"Investigative study of various activation functions for speech recognition","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2766609943","doi":"https://doi.org/10.1109/ncc.2017.8077043","mag":"2766609943"},"language":"en","primary_location":{"id":"doi:10.1109/ncc.2017.8077043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncc.2017.8077043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Twenty-third National Conference on Communications (NCC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5014351336","display_name":"Hari Krishna Vydana","orcid":"https://orcid.org/0000-0001-5192-5888"},"institutions":[{"id":"https://openalex.org/I64189192","display_name":"International Institute of Information Technology, Hyderabad","ror":"https://ror.org/05f11g639","country_code":"IN","type":"education","lineage":["https://openalex.org/I64189192"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Hari Krishna Vydana","raw_affiliation_strings":["Speech and Vision Laboratory, International Institute of Information Technology, Hyderabad, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Speech and Vision Laboratory, International Institute of Information Technology, Hyderabad, India","institution_ids":["https://openalex.org/I64189192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007569113","display_name":"Anil Kumar Vuppala","orcid":"https://orcid.org/0000-0001-7795-0408"},"institutions":[{"id":"https://openalex.org/I64189192","display_name":"International Institute of Information Technology, Hyderabad","ror":"https://ror.org/05f11g639","country_code":"IN","type":"education","lineage":["https://openalex.org/I64189192"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anil Kumar Vuppala","raw_affiliation_strings":["Speech and Vision Laboratory, International Institute of Information Technology, Hyderabad, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Speech and Vision Laboratory, International Institute of Information Technology, Hyderabad, India","institution_ids":["https://openalex.org/I64189192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I64189192"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9997000098228455,"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"}},{"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/T11309","display_name":"Music and Audio Processing","score":0.9966999888420105,"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/timit","display_name":"TIMIT","score":0.9272331595420837},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7343249320983887},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7286996245384216},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.7031289935112},{"id":"https://openalex.org/keywords/activation-function","display_name":"Activation function","score":0.6808558106422424},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6359230875968933},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5933432579040527},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5821361541748047},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5546697378158569},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5044301748275757},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.46171876788139343},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44062182307243347},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10998708009719849}],"concepts":[{"id":"https://openalex.org/C2778724510","wikidata":"https://www.wikidata.org/wiki/Q7670405","display_name":"TIMIT","level":3,"score":0.9272331595420837},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7343249320983887},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7286996245384216},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.7031289935112},{"id":"https://openalex.org/C38365724","wikidata":"https://www.wikidata.org/wiki/Q4677469","display_name":"Activation function","level":3,"score":0.6808558106422424},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6359230875968933},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5933432579040527},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5821361541748047},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5546697378158569},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5044301748275757},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.46171876788139343},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44062182307243347},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10998708009719849},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ncc.2017.8077043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncc.2017.8077043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Twenty-third National Conference on Communications (NCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W1533861849","https://openalex.org/W1661756259","https://openalex.org/W1677182931","https://openalex.org/W2069143585","https://openalex.org/W2072128103","https://openalex.org/W2110798204","https://openalex.org/W2136922672","https://openalex.org/W2156387975","https://openalex.org/W2160815625","https://openalex.org/W2176412452","https://openalex.org/W2963285578","https://openalex.org/W2963568027","https://openalex.org/W4231109964","https://openalex.org/W6600284362","https://openalex.org/W6631943919","https://openalex.org/W6636969168","https://openalex.org/W6676481782","https://openalex.org/W6682889407","https://openalex.org/W6685562342","https://openalex.org/W6715932150"],"related_works":["https://openalex.org/W2008638795","https://openalex.org/W2155033763","https://openalex.org/W2071828724","https://openalex.org/W1994694193","https://openalex.org/W1990589093","https://openalex.org/W1586532344","https://openalex.org/W2140027889","https://openalex.org/W2054353061","https://openalex.org/W2340308015","https://openalex.org/W2108688091"],"abstract_inverted_index":{"Significant":[0],"developments":[1,37],"in":[2,38,83],"deep":[3,31,39,67,132],"learning":[4,32,40,68],"methods":[5,69],"have":[6,139],"been":[7,24,76,140],"achieved":[8],"with":[9,43,135,171],"the":[10,28,36,44,51,63,84,106,144,164,176,182,190,194,202,216],"capability":[11],"to":[12,142,162,189,215],"train":[13],"more":[14],"deeper":[15],"networks.":[16,218],"The":[17,54],"performance":[18,183,210],"of":[19,30,35,46,56,65,80,86,108,147,166,184,204,211],"speech":[20,71,113,127,168],"recognition":[21,114,128,169],"system":[22],"has":[23,61,75],"greatly":[25],"improved":[26],"by":[27],"use":[29,64],"techniques.":[33],"Most":[34],"are":[41,160],"associated":[42],"development":[45,55,85],"new":[47],"activation":[48,87,110,137],"functions":[49,88,111,138],"and":[50,97,158],"corresponding":[52],"initializations.":[53],"Rectified":[57],"linear":[58],"units":[59,95],"(ReLU)":[60],"revolutionized":[62],"supervised":[66],"for":[70,193],"recognition.":[72],"Recently":[73],"there":[74],"a":[77,119],"great":[78],"deal":[79],"research":[81],"interest":[82],"Leaky-ReLU":[89],"(LReLU),":[90],"Parametric-ReLU":[91],"(PReLU),":[92],"Exponential":[93],"Linear":[94],"(ELU)":[96],"Parametric-ELU":[98],"(PELU).":[99],"This":[100],"work":[101],"is":[102,129,179,186,213],"aimed":[103],"at":[104],"studying":[105],"influence":[107],"various":[109,167],"on":[112],"system.":[115],"In":[116,151],"this":[117,152],"work,":[118,153],"hidden":[120,148],"Markov":[121,149],"model-Deep":[122],"neural":[123,133],"network":[124],"(HMM-DNN)":[125],"based":[126],"used,":[130],"where":[131],"networks":[134,192],"different":[136,172],"employed":[141,161],"obtain":[143],"emission":[145],"probabilities":[146],"model.":[150],"two":[154],"datasets":[155,203],"i.e.,":[156],"TIMIT":[157,199],"WSJ":[159],"study":[163],"behavior":[165],"systems":[170],"sized":[173,196],"datasets.":[174],"During":[175],"study,":[177],"it":[178],"observed":[180],"that":[181],"ReLU-networks":[185],"superior":[187,214],"compared":[188],"other":[191,217],"smaller":[195],"dataset":[197],"(i.e.,":[198,208],"dataset).":[200],"For":[201],"sufficiently":[205],"larger":[206],"size":[207],"WSJ)":[209],"ELU-networks":[212]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
