{"id":"https://openalex.org/W1884881496","doi":"https://doi.org/10.1109/icassp.1985.1168095","title":"Single chip implementation of feature measurement for LPC-based speech recognition","display_name":"Single chip implementation of feature measurement for LPC-based speech recognition","publication_year":2005,"publication_date":"2005-03-23","ids":{"openalex":"https://openalex.org/W1884881496","doi":"https://doi.org/10.1109/icassp.1985.1168095","mag":"1884881496"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1985.1168095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1985.1168095","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/A5013892797","display_name":"John G. Ackenhusen","orcid":null},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"J. Ackenhusen","raw_affiliation_strings":["Speech Processing Department, AT and T Bell Laboratories, Inc., Murray Hill, NJ, USA","AT&T Bell Laboratories, New Jersey"],"affiliations":[{"raw_affiliation_string":"Speech Processing Department, AT and T Bell Laboratories, Inc., Murray Hill, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"AT&T Bell Laboratories, New Jersey","institution_ids":["https://openalex.org/I1283103587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069516527","display_name":"Yujin Oh","orcid":"https://orcid.org/0000-0003-4319-8435"},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]},{"id":"https://openalex.org/I72090969","display_name":"Nokia (United States)","ror":"https://ror.org/038km2573","country_code":"US","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I72090969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Y. Oh","raw_affiliation_strings":["Speech Processing Department, AT and T Bell Laboratories, Inc., Murray Hill, NJ, USA","AT&T Bell Labs.#TAB#"],"affiliations":[{"raw_affiliation_string":"Speech Processing Department, AT and T Bell Laboratories, Inc., Murray Hill, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"AT&T Bell Labs.#TAB#","institution_ids":["https://openalex.org/I72090969"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5013892797"],"corresponding_institution_ids":["https://openalex.org/I1283103587"],"apc_list":null,"apc_paid":null,"fwci":0.5875,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.68103653,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":null,"first_page":"1445","last_page":"1448"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9934999942779541,"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":0.9916999936103821,"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":0.6797147989273071},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.5961594581604004},{"id":"https://openalex.org/keywords/chip","display_name":"Chip","score":0.5809358358383179},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5780102014541626},{"id":"https://openalex.org/keywords/linear-predictive-coding","display_name":"Linear predictive coding","score":0.5469416379928589},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5391703844070435},{"id":"https://openalex.org/keywords/voice-activity-detection","display_name":"Voice activity detection","score":0.46323248744010925},{"id":"https://openalex.org/keywords/speech-processing","display_name":"Speech processing","score":0.44494935870170593},{"id":"https://openalex.org/keywords/codec2","display_name":"Codec2","score":0.4324132800102234},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.41634422540664673},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10460224747657776},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08854246139526367}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6797147989273071},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.5961594581604004},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.5809358358383179},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5780102014541626},{"id":"https://openalex.org/C59883199","wikidata":"https://www.wikidata.org/wiki/Q1826438","display_name":"Linear predictive coding","level":3,"score":0.5469416379928589},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5391703844070435},{"id":"https://openalex.org/C204201278","wikidata":"https://www.wikidata.org/wiki/Q1332614","display_name":"Voice activity detection","level":3,"score":0.46323248744010925},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.44494935870170593},{"id":"https://openalex.org/C75217168","wikidata":"https://www.wikidata.org/wiki/Q1105653","display_name":"Codec2","level":4,"score":0.4324132800102234},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.41634422540664673},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10460224747657776},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08854246139526367},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.1985.1168095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1985.1168095","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/16","display_name":"Peace, Justice and strong institutions","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1542588102","https://openalex.org/W2496295964","https://openalex.org/W1976952689","https://openalex.org/W1589226984","https://openalex.org/W2910493550","https://openalex.org/W2151333624","https://openalex.org/W1999835922","https://openalex.org/W1984921740","https://openalex.org/W4319347033","https://openalex.org/W2154415461"],"abstract_inverted_index":{"A":[0],"single":[1],"chip":[2],"implementation":[3,156],"of":[4,67,85,96,106,115,122,128,165,179],"LPC-based":[5,77,146],"feature":[6,31,64,100],"measurement":[7,32,101],"has":[8,20,131],"been":[9,21,132],"developed":[10],"using":[11],"the":[12,35,68,107,129],"AT&T":[13],"Bell":[14],"Laboratories":[15],"Digital":[16],"Signal":[17],"Processor":[18],"and":[19,27,61,75,120,154],"verified":[22],"by":[23],"both":[24],"numerical":[25],"simulation":[26,153],"system":[28],"use.":[29],"The":[30,99,126],"circuit,":[33],"called":[34],"FXDSP,":[36],"performs":[37],"eighth-order":[38],"LPC":[39],"analysis":[40,83],"continuously":[41,91],"in":[42,110,174],"real":[43,124],"time.":[44,125],"It":[45],"receives":[46],"mu-law-encoded":[47],"telephone":[48],"bandwidth":[49],"speech":[50,143,175],"at":[51,92],"a":[52,58,63,93,135],"6.667":[53],"kHz":[54],"sampling":[55],"rate":[56],"from":[57],"standard":[59],"CODEC":[60],"produces":[62],"vector":[65],"consisting":[66],"log":[69,147],"energy,":[70],"nine":[71,76],"amplitude-normalized":[72],"autocorrelation":[73],"coefficients,":[74],"test":[78],"pattern":[79],"coefficients":[80],"for":[81,171],"each":[82],"frame":[84,94],"speech.":[86],"Feature":[87],"vectors":[88],"are":[89],"output":[90,127],"period":[95],"15":[97],"msec.":[98],"program":[102,112,139],"requires":[103],"1023":[104],"locations":[105],"1024":[108],"available":[109,117,123],"on-chip":[111],"ROM,":[113],"211":[114],"256":[116],"RAM":[118],"locations,":[119],"75%":[121],"FXDSP":[130,155],"compared":[133,168],"to":[134,159],"floating":[136,151],"point":[137,152],"FORTRAN":[138],"calculating":[140],"on":[141],"identical":[142],"waveforms.":[144],"An":[145],"likelihood":[148],"distance":[149,164,178],"between":[150],"was":[157],"found":[158],"be":[160],"negligibly":[161],"small":[162],"(average":[163,177],"0.021)":[166],"when":[167],"with":[169],"distances":[170],"word":[172],"matches":[173],"recognition":[176],"0.45).":[180]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
