{"id":"https://openalex.org/W2548268919","doi":"https://doi.org/10.1109/icacci.2016.7732362","title":"Optimizing feature extraction techniques constituting phone based modelling on connected words for Punjabi automatic speech recognition","display_name":"Optimizing feature extraction techniques constituting phone based modelling on connected words for Punjabi automatic speech recognition","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2548268919","doi":"https://doi.org/10.1109/icacci.2016.7732362","mag":"2548268919"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2016.7732362","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2016.7732362","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5102818557","display_name":"Arshpreet Kaur","orcid":null},"institutions":[{"id":"https://openalex.org/I74319210","display_name":"Chitkara University","ror":"https://ror.org/057d6z539","country_code":"IN","type":"education","lineage":["https://openalex.org/I74319210"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arshpreet Kaur","raw_affiliation_strings":["School of Computer Sciences Chitkara University, Punjab, INDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Sciences Chitkara University, Punjab, INDIA","institution_ids":["https://openalex.org/I74319210"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085144343","display_name":"Amitoj Singh","orcid":"https://orcid.org/0000-0002-5884-3145"},"institutions":[{"id":"https://openalex.org/I74319210","display_name":"Chitkara University","ror":"https://ror.org/057d6z539","country_code":"IN","type":"education","lineage":["https://openalex.org/I74319210"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Amitoj Singh","raw_affiliation_strings":["CURIN Chitkara University, Punjab, INDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CURIN Chitkara University, Punjab, INDIA","institution_ids":["https://openalex.org/I74319210"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8833,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.84845581,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2104","last_page":"2108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9998999834060669,"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":0.998199999332428,"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/computer-science","display_name":"Computer science","score":0.7951663136482239},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7790533900260925},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.7244478464126587},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.7193204760551453},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.6057682633399963},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5939733982086182},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5107724666595459},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.4908038079738617},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.4683486819267273},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4241299033164978},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.41179144382476807},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3374977707862854},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.0879623293876648}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7951663136482239},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7790533900260925},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.7244478464126587},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.7193204760551453},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.6057682633399963},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5939733982086182},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5107724666595459},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.4908038079738617},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.4683486819267273},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4241299033164978},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41179144382476807},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3374977707862854},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0879623293876648},{"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/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/icacci.2016.7732362","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2016.7732362","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Gender equality","score":0.550000011920929,"id":"https://metadata.un.org/sdg/5"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1533883318","https://openalex.org/W2009106392","https://openalex.org/W2047769394","https://openalex.org/W2069431997","https://openalex.org/W2088489891","https://openalex.org/W2090861223","https://openalex.org/W2115299561","https://openalex.org/W2148154194","https://openalex.org/W2151484683","https://openalex.org/W2158273884","https://openalex.org/W2169890399","https://openalex.org/W2170781540","https://openalex.org/W4256112632","https://openalex.org/W6631901108","https://openalex.org/W6677139582"],"related_works":["https://openalex.org/W3107474891","https://openalex.org/W2029924358","https://openalex.org/W2411953906","https://openalex.org/W2131226854","https://openalex.org/W2131735617","https://openalex.org/W2911335828","https://openalex.org/W294719094","https://openalex.org/W2373006798","https://openalex.org/W2167236583","https://openalex.org/W3197541072"],"abstract_inverted_index":{"Punjabi":[0,81,161,195],"phoneme":[1],"sounds":[2],"are":[3,163],"tonal":[4],"in":[5,9,28,37,187],"nature":[6,179],"which":[7],"dissent":[8],"most":[10],"regions":[11],"of":[12,42,52,73,98,109,147,155,180],"Punjab.":[13],"Recent":[14],"research":[15],"works":[16],"reveal":[17],"less":[18],"significant":[19],"work":[20,31],"done":[21,32],"towards":[22],"developing":[23],"a":[24,138,152,189],"speech":[25,110,191],"recognition":[26,192],"system":[27,75,193],"Punjabi.":[29],"The":[30],"will":[33,185],"feature":[34,44],"out":[35],"variability":[36],"the":[38,50,70,74,96,107,112,143,174,178],"correctness":[39,146],"and":[40,90,104,132,145,182],"accuracy":[41,144,156],"various":[43],"extraction":[45],"techniques.":[46],"Following":[47],"paper":[48],"objects":[49],"application":[51],"Automatic":[53],"Speech":[54],"Recognition":[55],"on":[56,63,142,177],"connected":[57],"words":[58,82],"instituting":[59],"HTK":[60],"toolkit":[61],"modelled":[62],"Hidden":[64],"Markov":[65],"Model":[66],"(HMM)":[67],"to":[68,165],"build":[69],"system.":[71],"Back-end":[72],"was":[76],"braced":[77],"for":[78,95,160,194],"150":[79],"distinct":[80,85],"from":[83,87],"16":[84],"speakers":[86,92],"noise-free":[88],"corpus":[89,100],"12":[91],"were":[93],"indulged":[94],"collection":[97],"noisy":[99],"including":[101],"both":[102],"male":[103],"female.":[105],"In":[106],"phrase":[108],"recognition,":[111],"proposed":[113],"Feature":[114],"Extractor":[115],"we":[116],"use":[117],"Front":[118],"end":[119],"techniques":[120],"as":[121],"\u201cpower":[122],"normalized":[123],"cepstral":[124,129],"coefficients":[125,130],"(PNCC)\u201d,":[126],"\u201cMel":[127],"frequency":[128],"(MFCC)\u201d":[131],"\u201cPerceptual":[133],"Linear":[134],"Prediction":[135],"(PLP)\u201d":[136],"following":[137],"statistical":[139],"comparison":[140,175],"based":[141,176],"results":[148],"attained.":[149],"To":[150],"attain":[151],"higher":[153],"rate":[154],"level":[157],"34":[158],"phones":[159],"language":[162],"used":[164],"break":[166],"each":[167],"word":[168],"into":[169],"small":[170],"sound":[171],"frames.":[172],"Hence,":[173],"training":[181],"testing":[183],"environment":[184],"aid":[186],"framing":[188],"vital":[190],"language.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
