{"id":"https://openalex.org/W1978316861","doi":"https://doi.org/10.1109/fuzz-ieee.2013.6622465","title":"Automatic text independent language identification using reduct set of feature vectors","display_name":"Automatic text independent language identification using reduct set of feature vectors","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W1978316861","doi":"https://doi.org/10.1109/fuzz-ieee.2013.6622465","mag":"1978316861"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2013.6622465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2013.6622465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","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/A5113534544","display_name":"M. Sadanandam","orcid":null},"institutions":[{"id":"https://openalex.org/I28210344","display_name":"Kakatiya University","ror":"https://ror.org/012zpbg81","country_code":"IN","type":"education","lineage":["https://openalex.org/I28210344"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"M. Sadanandam","raw_affiliation_strings":["CSE, Kakatiya University, Warangal, Andhra Pradesh, India","CSE Kakatiya Univ., Warangal, India"],"affiliations":[{"raw_affiliation_string":"CSE, Kakatiya University, Warangal, Andhra Pradesh, India","institution_ids":["https://openalex.org/I28210344"]},{"raw_affiliation_string":"CSE Kakatiya Univ., Warangal, India","institution_ids":["https://openalex.org/I28210344"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110244877","display_name":"V. Kamakshi Prasad","orcid":null},"institutions":[{"id":"https://openalex.org/I10874241","display_name":"Jawaharlal Nehru Technological University, Hyderabad","ror":"https://ror.org/002tchr49","country_code":"IN","type":"education","lineage":["https://openalex.org/I10874241"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"V. Kamakshi Prasad","raw_affiliation_strings":["CSE, Jawaharlal Nehru Technological University, Hyderabad, Andhra Pradesh, India","CSE Jawaharlal Nehru Technol. Univ. Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"CSE, Jawaharlal Nehru Technological University, Hyderabad, Andhra Pradesh, India","institution_ids":["https://openalex.org/I10874241"]},{"raw_affiliation_string":"CSE Jawaharlal Nehru Technol. Univ. Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I10874241"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5113534544"],"corresponding_institution_ids":["https://openalex.org/I28210344"],"apc_list":null,"apc_paid":null,"fwci":0.3625,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61313025,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"14","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9901999831199646,"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/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9850000143051147,"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/reduct","display_name":"Reduct","score":0.9742307662963867},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6536128520965576},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6523751020431519},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.595616340637207},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5916361212730408},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5566846132278442},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.534204363822937},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5211132168769836},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.47422146797180176},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4621696174144745},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4503830075263977},{"id":"https://openalex.org/keywords/formant","display_name":"Formant","score":0.44203075766563416},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.42916417121887207},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.37452927231788635},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2528718113899231}],"concepts":[{"id":"https://openalex.org/C69177213","wikidata":"https://www.wikidata.org/wiki/Q12880812","display_name":"Reduct","level":3,"score":0.9742307662963867},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6536128520965576},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6523751020431519},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.595616340637207},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5916361212730408},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5566846132278442},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.534204363822937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5211132168769836},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.47422146797180176},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4621696174144745},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4503830075263977},{"id":"https://openalex.org/C158215666","wikidata":"https://www.wikidata.org/wiki/Q1414685","display_name":"Formant","level":3,"score":0.44203075766563416},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.42916417121887207},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.37452927231788635},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2528718113899231},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2779581591","wikidata":"https://www.wikidata.org/wiki/Q36244","display_name":"Vowel","level":2,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/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/fuzz-ieee.2013.6622465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2013.6622465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1586702941","https://openalex.org/W1638980978","https://openalex.org/W1976761624","https://openalex.org/W1982908312","https://openalex.org/W2003007256","https://openalex.org/W2004524042","https://openalex.org/W2021189532","https://openalex.org/W2029776772","https://openalex.org/W2042237244","https://openalex.org/W2066718061","https://openalex.org/W2095501777","https://openalex.org/W2137205163","https://openalex.org/W2138659827","https://openalex.org/W2168186580","https://openalex.org/W2172287020","https://openalex.org/W3140882520","https://openalex.org/W4255833381","https://openalex.org/W4285719527","https://openalex.org/W6635150843"],"related_works":["https://openalex.org/W2369301332","https://openalex.org/W2101726329","https://openalex.org/W2376860763","https://openalex.org/W1975980892","https://openalex.org/W2163171169","https://openalex.org/W2010504013","https://openalex.org/W1880013533","https://openalex.org/W2535769210","https://openalex.org/W1540858424","https://openalex.org/W2393055956"],"abstract_inverted_index":{"In":[0,72],"this":[1,46],"paper,":[2],"robust":[3],"features":[4,32],"are":[5,23,33,86,113,125],"proposed":[6,108],"for":[7],"spoken":[8],"language":[9],"identification":[10],"(LID)":[11],"system.":[12,110],"12":[13],"Mel":[14],"frequency":[15],"cepstral":[16],"coefficients":[17],"(MFCCs)":[18],"and":[19,76,103,122],"five":[20],"formant":[21],"frequencies":[22],"extracted":[24],"from":[25,45],"each":[26],"short-time":[27],"windowed":[28],"speech":[29,117],"signal.":[30],"These":[31],"concatenated":[34],"to":[35,89],"form":[36],"17-dimensional":[37,47],"feature":[38,48,64,84],"vectors.":[39],"8-dimensional":[40,55],"reduct":[41,56,92],"set":[42,52,57],"is":[43,58,95],"obtained":[44],"vector":[49],"using":[50,66],"rough":[51],"theory.":[53],"This":[54],"transformed":[59],"into":[60],"15":[61,82],"dimensional":[62,83],"new":[63],"vectors":[65,85],"the":[67,74,107,123],"approach":[68],"followed":[69],"in":[70,101],"[1].":[71],"both":[73],"training":[75,102],"testing":[77,104],"phases":[78,105],"of":[79,91,99,106,119],"LID,":[80],"these":[81],"used.":[87],"Due":[88],"usage":[90],"set,":[93],"there":[94],"a":[96],"significant":[97],"reduction":[98],"time":[100],"LID":[109],"The":[111],"experiments":[112],"carried":[114],"out":[115],"on":[116],"database":[118],"Indian":[120],"languages":[121],"results":[124],"impressive.":[126]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}