{"id":"https://openalex.org/W1919072383","doi":"https://doi.org/10.1109/icassp.1985.1168471","title":"Speech recognition in the F-16 cockpit using principal spectral components","display_name":"Speech recognition in the F-16 cockpit using principal spectral components","publication_year":2005,"publication_date":"2005-03-23","ids":{"openalex":"https://openalex.org/W1919072383","doi":"https://doi.org/10.1109/icassp.1985.1168471","mag":"1919072383"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1985.1168471","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1985.1168471","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing","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/A5109242891","display_name":"P.K. Rajasekaran","orcid":null},"institutions":[{"id":"https://openalex.org/I74760111","display_name":"Texas Instruments (United States)","ror":"https://ror.org/03vsmv677","country_code":"US","type":"company","lineage":["https://openalex.org/I74760111"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"P. Rajasekaran","raw_affiliation_strings":["Central Research Laboratories, Texas Instruments, Inc., Dallas, TX, USA","Texas Instruments Incorporated, Dallas, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Central Research Laboratories, Texas Instruments, Inc., Dallas, TX, USA","institution_ids":["https://openalex.org/I74760111"]},{"raw_affiliation_string":"Texas Instruments Incorporated, Dallas, Texas, USA","institution_ids":["https://openalex.org/I74760111"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082356959","display_name":"George R. Doddington","orcid":null},"institutions":[{"id":"https://openalex.org/I74760111","display_name":"Texas Instruments (United States)","ror":"https://ror.org/03vsmv677","country_code":"US","type":"company","lineage":["https://openalex.org/I74760111"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"G. Doddington","raw_affiliation_strings":["Central Research Laboratories, Texas Instruments, Inc., Dallas, TX, USA","Central Res. Lab., Texas Instrum. Inc., Dallas, TX, USA"],"affiliations":[{"raw_affiliation_string":"Central Research Laboratories, Texas Instruments, Inc., Dallas, TX, USA","institution_ids":["https://openalex.org/I74760111"]},{"raw_affiliation_string":"Central Res. Lab., Texas Instrum. Inc., Dallas, TX, USA","institution_ids":["https://openalex.org/I74760111"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5109242891"],"corresponding_institution_ids":["https://openalex.org/I74760111"],"apc_list":null,"apc_paid":null,"fwci":2.2255,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.87586047,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"10","issue":null,"first_page":"882","last_page":"885"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9970999956130981,"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/T10860","display_name":"Speech and Audio Processing","score":0.9970999956130981,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.991100013256073,"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/speech-recognition","display_name":"Speech recognition","score":0.7373281121253967},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6589936017990112},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.642280638217926},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5995709896087646},{"id":"https://openalex.org/keywords/filter-bank","display_name":"Filter bank","score":0.5707294940948486},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5171141624450684},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5125045776367188},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4962533116340637},{"id":"https://openalex.org/keywords/uncorrelated","display_name":"Uncorrelated","score":0.4766693413257599},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4617280066013336},{"id":"https://openalex.org/keywords/cockpit","display_name":"Cockpit","score":0.4277636408805847},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4238499402999878},{"id":"https://openalex.org/keywords/linear-prediction","display_name":"Linear prediction","score":0.4121139645576477},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38745197653770447},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2786106765270233},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1447526514530182},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1268845498561859},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08313703536987305}],"concepts":[{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7373281121253967},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6589936017990112},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.642280638217926},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5995709896087646},{"id":"https://openalex.org/C100515483","wikidata":"https://www.wikidata.org/wiki/Q3268235","display_name":"Filter bank","level":3,"score":0.5707294940948486},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5171141624450684},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5125045776367188},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4962533116340637},{"id":"https://openalex.org/C169345407","wikidata":"https://www.wikidata.org/wiki/Q8216221","display_name":"Uncorrelated","level":2,"score":0.4766693413257599},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4617280066013336},{"id":"https://openalex.org/C30322324","wikidata":"https://www.wikidata.org/wiki/Q194156","display_name":"Cockpit","level":2,"score":0.4277636408805847},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4238499402999878},{"id":"https://openalex.org/C131109320","wikidata":"https://www.wikidata.org/wiki/Q581012","display_name":"Linear prediction","level":2,"score":0.4121139645576477},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38745197653770447},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2786106765270233},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1447526514530182},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1268845498561859},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08313703536987305},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.1985.1168471","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1985.1168471","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.550000011920929,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W1992468098","https://openalex.org/W2001850558","https://openalex.org/W2137089646","https://openalex.org/W2141968115"],"related_works":["https://openalex.org/W289003589","https://openalex.org/W2350798740","https://openalex.org/W4285264191","https://openalex.org/W2998452958","https://openalex.org/W2006341478","https://openalex.org/W2548061885","https://openalex.org/W333251188","https://openalex.org/W3180504149","https://openalex.org/W2036761630","https://openalex.org/W2216022431"],"abstract_inverted_index":{"A":[0],"modification":[1],"of":[2,37,50,72,96,112,114],"the":[3,38,59,110,115],"usual":[4],"LPC":[5,21,117],"speaker-dependent":[6],"speech":[7],"recognition":[8,13],"algorithms":[9],"yielded":[10,107],"significantly":[11],"improved":[12],"performance":[14],"in":[15,84,94],"an":[16],"F-16":[17],"fighter":[18],"cockpit":[19],"environment.The":[20],"model":[22],"is":[23],"first":[24],"transformed":[25],"into":[26],"spectral":[27,44],"amplitudes":[28,41],"using":[29],"asimulated":[30],"filter":[31,39],"bank.":[32],"Statistically":[33],"optimum":[34],"linear":[35],"transformation":[36],"bank":[40],"to":[42],"\"principal":[43],"components\"":[45],"(PSC)":[46],"provides":[47],"a":[48,77],"set":[49],"uncorrelated":[51],"features.":[52],"These":[53],"features":[54,62],"are":[55,63],"rank":[56],"ordered":[57],"and":[58,89,99],"least":[60],"significant":[61],"discarded.":[64],"The":[65,104],"data":[66],"base":[67],"used":[68],"for":[69,82,92],"experiments":[70],"consisted":[71],"5":[73],"male":[74],"speakers":[75],"uttering":[76],"70-word":[78],"vocabulary":[79],"ten":[80],"times":[81,91],"training":[83],"85":[85],"dBA":[86,101],"noise":[87,102],"level,":[88],"3":[90],"test":[93],"each":[95],"97,":[97],"106":[98],"112":[100],"levels.":[103],"PSC":[105],"method":[106],"about":[108],"half":[109],"number":[111],"substitutions":[113],"standard":[116],"method.":[118]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
