{"id":"https://openalex.org/W2210543936","doi":"https://doi.org/10.1109/spa.2015.7365136","title":"Robustness analysis of automatic speech signal recognition system against factors degrading speech signal","display_name":"Robustness analysis of automatic speech signal recognition system against factors degrading speech signal","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2210543936","doi":"https://doi.org/10.1109/spa.2015.7365136","mag":"2210543936"},"language":"en","primary_location":{"id":"doi:10.1109/spa.2015.7365136","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spa.2015.7365136","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","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/A5031158362","display_name":"Jaroslaw Oska","orcid":null},"institutions":[{"id":"https://openalex.org/I2800249161","display_name":"Military University of Technology in Warsaw","ror":"https://ror.org/05fct5h31","country_code":"PL","type":"education","lineage":["https://openalex.org/I2800249161"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Jaroslaw Oska","raw_affiliation_strings":["Faculty of Electronics, Military University of Technology, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electronics, Military University of Technology, Warsaw, Poland","institution_ids":["https://openalex.org/I2800249161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059676472","display_name":"Jaros\u0142aw Wojtu\u0144","orcid":"https://orcid.org/0000-0003-0473-2316"},"institutions":[{"id":"https://openalex.org/I2800249161","display_name":"Military University of Technology in Warsaw","ror":"https://ror.org/05fct5h31","country_code":"PL","type":"education","lineage":["https://openalex.org/I2800249161"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Jaroslaw Wojtun","raw_affiliation_strings":["Faculty of Electronics, Military University of Technology, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electronics, Military University of Technology, Warsaw, Poland","institution_ids":["https://openalex.org/I2800249161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081927759","display_name":"Krzysztof Wodecki","orcid":null},"institutions":[{"id":"https://openalex.org/I2800249161","display_name":"Military University of Technology in Warsaw","ror":"https://ror.org/05fct5h31","country_code":"PL","type":"education","lineage":["https://openalex.org/I2800249161"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Krzysztof Wodecki","raw_affiliation_strings":["Faculty of Electronics, Military University of Technology, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electronics, Military University of Technology, Warsaw, Poland","institution_ids":["https://openalex.org/I2800249161"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075386896","display_name":"Zbigniew Piotrowski","orcid":"https://orcid.org/0000-0003-3556-0297"},"institutions":[{"id":"https://openalex.org/I2800249161","display_name":"Military University of Technology in Warsaw","ror":"https://ror.org/05fct5h31","country_code":"PL","type":"education","lineage":["https://openalex.org/I2800249161"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Zbigniew Piotrowski","raw_affiliation_strings":["Faculty of Electronics, Military University of Technology, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electronics, Military University of Technology, Warsaw, Poland","institution_ids":["https://openalex.org/I2800249161"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2800249161"],"apc_list":null,"apc_paid":null,"fwci":0.2058,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46503339,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"6","issue":null,"first_page":"71","last_page":"75"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9800999760627747,"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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9800999760627747,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9739000201225281,"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":0.9487000107765198,"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/speech-recognition","display_name":"Speech recognition","score":0.7583121061325073},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7239489555358887},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.7117491364479065},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7077131271362305},{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.5665839314460754},{"id":"https://openalex.org/keywords/linear-predictive-coding","display_name":"Linear predictive coding","score":0.5642077326774597},{"id":"https://openalex.org/keywords/linear-prediction","display_name":"Linear prediction","score":0.5099478960037231},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.48519423604011536},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.44793379306793213},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.44626328349113464},{"id":"https://openalex.org/keywords/cepstrum","display_name":"Cepstrum","score":0.41809818148612976},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4118228554725647},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.3908540606498718},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.389822781085968},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.2873649597167969}],"concepts":[{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7583121061325073},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7239489555358887},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.7117491364479065},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7077131271362305},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.5665839314460754},{"id":"https://openalex.org/C59883199","wikidata":"https://www.wikidata.org/wiki/Q1826438","display_name":"Linear predictive coding","level":3,"score":0.5642077326774597},{"id":"https://openalex.org/C131109320","wikidata":"https://www.wikidata.org/wiki/Q581012","display_name":"Linear prediction","level":2,"score":0.5099478960037231},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.48519423604011536},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.44793379306793213},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.44626328349113464},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.41809818148612976},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4118228554725647},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.3908540606498718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.389822781085968},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2873649597167969},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/spa.2015.7365136","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spa.2015.7365136","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W872800491","https://openalex.org/W1493366657","https://openalex.org/W1552314771","https://openalex.org/W1586390982","https://openalex.org/W1689977300","https://openalex.org/W1972303300","https://openalex.org/W2089683113","https://openalex.org/W2096942962","https://openalex.org/W2149132877","https://openalex.org/W2151662931","https://openalex.org/W2164057893","https://openalex.org/W2319652145","https://openalex.org/W2494231988","https://openalex.org/W2911617535","https://openalex.org/W4246275837","https://openalex.org/W6623815785","https://openalex.org/W6629690605","https://openalex.org/W6635027519","https://openalex.org/W6674278843"],"related_works":["https://openalex.org/W2363056088","https://openalex.org/W2363301696","https://openalex.org/W2808395304","https://openalex.org/W4312036005","https://openalex.org/W1921152853","https://openalex.org/W1994313308","https://openalex.org/W2383072803","https://openalex.org/W2352223112","https://openalex.org/W1570840316","https://openalex.org/W1949563597"],"abstract_inverted_index":{"In":[0,32],"the":[1,6,11,14,25,33,35,43,67,92],"article":[2],"there":[3],"are":[4],"presented":[5],"results":[7],"of":[8,13,27,37,46,69,95],"research":[9,34,63,88],"on":[10,24,66,91],"influence":[12],"lossy":[15],"compression,":[16],"used":[17],"in":[18,42],"codecs":[19],"G.711,":[20],"G.723.1":[21],"and":[22,50],"iLBC,":[23],"efficiency":[26],"isolated":[28,97],"speech":[29,98],"phrase":[30],"recognition.":[31],"degree":[36],"robustness":[38],"against":[39],"degrading":[40],"factors":[41],"parameterisation":[44],"method":[45],"audio":[47],"signal":[48],"LPCC":[49],"MFCC":[51],"(Linear":[52],"Prediction":[53],"Cepstral":[54,58],"Coefficients,":[55],"Mel":[56],"Frequency":[57],"Coefficients)":[59],"is":[60,64],"compared.":[61],"The":[62,87],"based":[65],"classifier":[68],"improved":[70],"Gaussian":[71],"mixtures":[72],"making":[73],"allowance":[74],"for":[75],"Universal":[76,84],"Background":[77,85],"Model":[78,82],"GMM-UBM":[79],"(Gaussian":[80],"Mixtures":[81],"-":[83],"Model).":[86],"was":[89],"conducted":[90],"database":[93],"composed":[94],"3000":[96],"phrases.":[99]},"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
