{"id":"https://openalex.org/W2030444545","doi":"https://doi.org/10.1109/is.2012.6335121","title":"Reducing speech recognition costs: By compressing the input data","display_name":"Reducing speech recognition costs: By compressing the input data","publication_year":2012,"publication_date":"2012-09-01","ids":{"openalex":"https://openalex.org/W2030444545","doi":"https://doi.org/10.1109/is.2012.6335121","mag":"2030444545"},"language":"en","primary_location":{"id":"doi:10.1109/is.2012.6335121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/is.2012.6335121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 6th IEEE INTERNATIONAL CONFERENCE INTELLIGENT SYSTEMS","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/A5055216705","display_name":"Ramin Halavati","orcid":null},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Ramin Halavati","raw_affiliation_strings":["Electrical Engineering Department, Sharif University of Technology, Tehran, Iran","[Electrical Engineering Dept., Sharif University of Technology, Tehran, Iran]"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]},{"raw_affiliation_string":"[Electrical Engineering Dept., Sharif University of Technology, Tehran, Iran]","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103264222","display_name":"Saeed Bagheri Shouraki","orcid":"https://orcid.org/0000-0001-9865-8916"},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Saeed Bagheri Shouraki","raw_affiliation_strings":["Electrical Engineering Department, Sharif University of Technology, Tehran, Iran","[Electrical Engineering Dept., Sharif University of Technology, Tehran, Iran]"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]},{"raw_affiliation_string":"[Electrical Engineering Dept., Sharif University of Technology, Tehran, Iran]","institution_ids":["https://openalex.org/I133529467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5055216705"],"corresponding_institution_ids":["https://openalex.org/I133529467"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.11352581,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"3","issue":null,"first_page":"102","last_page":"107"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9980999827384949,"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/T11309","display_name":"Music and Audio Processing","score":0.9980999827384949,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9979000091552734,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9976000189781189,"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/computer-science","display_name":"Computer science","score":0.7845593094825745},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6685901880264282},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.658147394657135},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6129551529884338},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5842589139938354},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5180542469024658},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48829197883605957},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46962833404541016},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.45292723178863525},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4233623445034027},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1938881278038025},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12049677968025208},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11835062503814697}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7845593094825745},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6685901880264282},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.658147394657135},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6129551529884338},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5842589139938354},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5180542469024658},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48829197883605957},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46962833404541016},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.45292723178863525},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4233623445034027},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1938881278038025},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12049677968025208},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11835062503814697},{"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},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/is.2012.6335121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/is.2012.6335121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 6th IEEE INTERNATIONAL CONFERENCE INTELLIGENT SYSTEMS","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.420.9473","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.420.9473","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www-gth.die.upm.es/research/documentation/Hal_Red.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W89602566","https://openalex.org/W1490760466","https://openalex.org/W1529663760","https://openalex.org/W1879384868","https://openalex.org/W1984446451","https://openalex.org/W2102687237","https://openalex.org/W2107338293","https://openalex.org/W2110690497","https://openalex.org/W2110707300","https://openalex.org/W2124243855","https://openalex.org/W2125369829","https://openalex.org/W2132599149","https://openalex.org/W2133128274","https://openalex.org/W2136571737","https://openalex.org/W2146173625","https://openalex.org/W2146558587","https://openalex.org/W2156561020","https://openalex.org/W2158358098","https://openalex.org/W2160610099","https://openalex.org/W2160784155","https://openalex.org/W2163929346","https://openalex.org/W2164463707","https://openalex.org/W2171684698","https://openalex.org/W2396408141","https://openalex.org/W2406777461","https://openalex.org/W2585866846","https://openalex.org/W4205687621","https://openalex.org/W6603625576","https://openalex.org/W6676284021","https://openalex.org/W6683609670"],"related_works":["https://openalex.org/W2349784553","https://openalex.org/W4298130764","https://openalex.org/W3022596247","https://openalex.org/W2601444686","https://openalex.org/W2804364458","https://openalex.org/W4307058054","https://openalex.org/W4292238148","https://openalex.org/W4323660495","https://openalex.org/W2132641928","https://openalex.org/W1997182898"],"abstract_inverted_index":{"One":[0],"of":[1,5,47,82,113,122],"the":[2,12,26,33,58,109,119],"key":[3],"constraints":[4],"using":[6],"embedded":[7],"speech":[8,27],"recognition":[9,34,78,83,92],"modules":[10],"is":[11,38,105,125],"required":[13],"computational":[14],"power.":[15],"To":[16],"decrease":[17],"this":[18],"requirement,":[19],"we":[20],"propose":[21],"an":[22],"algorithm":[23,37],"that":[24,57],"clusters":[25],"signal":[28],"before":[29],"passing":[30],"it":[31],"to":[32,73,89,95,108],"units.":[35],"The":[36],"based":[39],"on":[40,71],"agglomerative":[41],"clustering":[42],"and":[43],"produces":[44],"a":[45,62],"sequence":[46],"compressed":[48],"frames,":[49],"optimized":[50],"for":[51],"recognition.":[52],"Our":[53],"experimental":[54],"results":[55],"indicate":[56],"proposed":[59],"method":[60],"presents":[61],"frame":[63,100],"rate":[64,101],"with":[65],"average":[66],"40":[67],"frames":[68,115,128],"per":[69,116,129],"second":[70,117],"medium":[72],"large":[74],"vocabulary":[75],"isolated":[76],"word":[77],"tasks":[79],"without":[80],"loss":[81],"accuracy":[84],"which":[85],"result":[86,121],"in":[87,93],"up":[88],"60%":[90],"faster":[91],"compare":[94],"usual":[96],"100":[97],"fps":[98],"fixed":[99],"sampling.":[102],"This":[103],"value":[104,112],"quite":[106],"close":[107],"theoretically":[110],"optimal":[111],"37.5":[114],"while":[118],"best":[120],"former":[123],"approaches":[124],"about":[126],"60":[127],"second.":[130]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}