{"id":"https://openalex.org/W2103916214","doi":"https://doi.org/10.1109/icassp.1986.1169255","title":"Vector adaptive predictive coding of speech at 9.6 kb/s","display_name":"Vector adaptive predictive coding of speech at 9.6 kb/s","publication_year":2005,"publication_date":"2005-03-24","ids":{"openalex":"https://openalex.org/W2103916214","doi":"https://doi.org/10.1109/icassp.1986.1169255","mag":"2103916214"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1986.1169255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1986.1169255","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5065966638","display_name":"Juin-Hwey Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Juin-Hwey Chen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016272725","display_name":"A. Gersho","orcid":null},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A. Gersho","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154570441"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"1693","last_page":"1696"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":1.0,"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":1.0,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9876999855041504,"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/T11034","display_name":"Digital Filter Design and Implementation","score":0.9869999885559082,"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/code-excited-linear-prediction","display_name":"Code-excited linear prediction","score":0.9330638647079468},{"id":"https://openalex.org/keywords/vector-sum-excited-linear-prediction","display_name":"Vector sum excited linear prediction","score":0.7633672952651978},{"id":"https://openalex.org/keywords/linear-predictive-coding","display_name":"Linear predictive coding","score":0.68000328540802},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6738467812538147},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.6618313193321228},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6365119814872742},{"id":"https://openalex.org/keywords/harmonic-vector-excitation-coding","display_name":"Harmonic Vector Excitation Coding","score":0.6095688343048096},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5852997303009033},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.544159471988678},{"id":"https://openalex.org/keywords/linear-prediction","display_name":"Linear prediction","score":0.5188847184181213},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5060753226280212},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.4248017966747284}],"concepts":[{"id":"https://openalex.org/C105964291","wikidata":"https://www.wikidata.org/wiki/Q856184","display_name":"Code-excited linear prediction","level":4,"score":0.9330638647079468},{"id":"https://openalex.org/C138807605","wikidata":"https://www.wikidata.org/wiki/Q7917845","display_name":"Vector sum excited linear prediction","level":5,"score":0.7633672952651978},{"id":"https://openalex.org/C59883199","wikidata":"https://www.wikidata.org/wiki/Q1826438","display_name":"Linear predictive coding","level":3,"score":0.68000328540802},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6738467812538147},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.6618313193321228},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6365119814872742},{"id":"https://openalex.org/C80167644","wikidata":"https://www.wikidata.org/wiki/Q463990","display_name":"Harmonic Vector Excitation Coding","level":3,"score":0.6095688343048096},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5852997303009033},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.544159471988678},{"id":"https://openalex.org/C131109320","wikidata":"https://www.wikidata.org/wiki/Q581012","display_name":"Linear prediction","level":2,"score":0.5188847184181213},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5060753226280212},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.4248017966747284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.1986.1169255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1986.1169255","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1591006912","https://openalex.org/W1904554885","https://openalex.org/W1970272279","https://openalex.org/W2002182716","https://openalex.org/W2033227994","https://openalex.org/W2037034710","https://openalex.org/W2048916503","https://openalex.org/W2096623674","https://openalex.org/W2100205678","https://openalex.org/W2135469284","https://openalex.org/W2151626637","https://openalex.org/W2584393883","https://openalex.org/W6635418751"],"related_works":["https://openalex.org/W2350749055","https://openalex.org/W1570840316","https://openalex.org/W1629698752","https://openalex.org/W1042315724","https://openalex.org/W2114934544","https://openalex.org/W2135307252","https://openalex.org/W2155796184","https://openalex.org/W2106797865","https://openalex.org/W2794974041","https://openalex.org/W2025826343"],"abstract_inverted_index":{"We":[0],"have":[1],"developed":[2],"a":[3,46,52,62,76,114],"new":[4],"speech":[5,27,109],"coder":[6],"which":[7],"significantly":[8],"enhances":[9],"Adaptive":[10],"Predictive":[11],"Coding":[12],"(APC)":[13],"by":[14,45,51,61,87],"using":[15],"vector":[16,64],"quantization.":[17],"The":[18,84],"coder,":[19],"called":[20],"Vector":[21],"APC":[22],"(VAPC),":[23],"gives":[24],"very":[25],"good":[26,34],"quality":[28,35],"at":[29,36,122],"9.6":[30],"kb/s":[31],"and":[32,49,107],"reasonably":[33],"4.8":[37],"kb/s.":[38],"In":[39,66],"VAPC,":[40],"redundancy":[41],"is":[42,58],"first":[43],"removed":[44],"long-delay":[47],"predictor":[48],"then":[50,59],"short-delay":[53],"predictor;":[54],"the":[55,67,81,92],"prediction":[56],"residual":[57,70],"quantized":[60],"gain-adaptive":[63],"quantizer.":[65],"receiver,":[68],"decoded":[69],"vectors":[71],"are":[72,89],"used":[73],"to":[74,79,96,117],"excite":[75],"synthesis":[77],"filter":[78],"obtain":[80],"coded":[82],"speech.":[83],"computations":[85],"required":[86],"VAPC":[88,111],"only":[90],"in":[91],"order":[93],"of":[94,103],"2":[95],"4":[97],"million":[98],"flops":[99],"per":[100],"second.":[101],"Because":[102],"its":[104],"low":[105,123],"complexity":[106],"high":[108],"quality,":[110],"may":[112],"offer":[113],"low-complexity":[115],"alternative":[116],"Code-Excited":[118],"Linear":[119],"Prediction":[120],"(CELP)":[121],"bit":[124],"rates.":[125]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
