{"id":"https://openalex.org/W203051973","doi":"https://doi.org/10.21437/interspeech.2009-755","title":"Discriminant spectrotemporal features for phoneme recognition","display_name":"Discriminant spectrotemporal features for phoneme recognition","publication_year":2009,"publication_date":"2009-09-06","ids":{"openalex":"https://openalex.org/W203051973","doi":"https://doi.org/10.21437/interspeech.2009-755","mag":"203051973"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2009-755","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2009-755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2009","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/A5033351155","display_name":"Nima Mesgarani","orcid":"https://orcid.org/0000-0002-2987-759X"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nima Mesgarani","raw_affiliation_strings":["Johns Hopkins University ("],"affiliations":[{"raw_affiliation_string":"Johns Hopkins University (","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109860004","display_name":"G. S. V. S. Sivaram","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"G. S. V. S. Sivaram","raw_affiliation_strings":["Johns Hopkins University ("],"affiliations":[{"raw_affiliation_string":"Johns Hopkins University (","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080686450","display_name":"Sridhar Krishna Nemala","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sridhar Krishna Nemala","raw_affiliation_strings":["Johns Hopkins University ("],"affiliations":[{"raw_affiliation_string":"Johns Hopkins University (","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038788686","display_name":"Mounya Elhilali","orcid":"https://orcid.org/0000-0003-2597-738X"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mounya Elhilali","raw_affiliation_strings":["Johns Hopkins University ("],"affiliations":[{"raw_affiliation_string":"Johns Hopkins University (","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042260050","display_name":"Hynek He\u0159mansk\u00fd","orcid":"https://orcid.org/0000-0001-8032-4811"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hynek Hermansky","raw_affiliation_strings":["Johns Hopkins University ("],"affiliations":[{"raw_affiliation_string":"Johns Hopkins University (","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5033351155"],"corresponding_institution_ids":["https://openalex.org/I145311948"],"apc_list":null,"apc_paid":null,"fwci":2.1148,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.85942362,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2983","last_page":"2986"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9988999962806702,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9984999895095825,"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/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.8676930665969849},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.7646682262420654},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6848281025886536},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6343495845794678},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6159030795097351},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5210058689117432},{"id":"https://openalex.org/keywords/multiple-discriminant-analysis","display_name":"Multiple discriminant analysis","score":0.48239314556121826},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.47247716784477234}],"concepts":[{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.8676930665969849},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.7646682262420654},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6848281025886536},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6343495845794678},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6159030795097351},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5210058689117432},{"id":"https://openalex.org/C58596280","wikidata":"https://www.wikidata.org/wiki/Q28324849","display_name":"Multiple discriminant analysis","level":3,"score":0.48239314556121826},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.47247716784477234}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2009-755","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2009-755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2009","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W9692546","https://openalex.org/W96378396","https://openalex.org/W1493591465","https://openalex.org/W1494019289","https://openalex.org/W1534605895","https://openalex.org/W2097349831","https://openalex.org/W2101596234","https://openalex.org/W2106939211","https://openalex.org/W2118695645","https://openalex.org/W2121283470","https://openalex.org/W2129476886","https://openalex.org/W2135055878","https://openalex.org/W2137075158","https://openalex.org/W2152295202"],"related_works":["https://openalex.org/W2063246903","https://openalex.org/W2375208160","https://openalex.org/W2350751952","https://openalex.org/W1984472287","https://openalex.org/W1999647744","https://openalex.org/W2544441948","https://openalex.org/W2104382484","https://openalex.org/W1978302214","https://openalex.org/W3008559849","https://openalex.org/W4238888834"],"abstract_inverted_index":{"We":[0],"propose":[1],"discriminant":[2,90],"methods":[3,57,76],"for":[4,9,58],"deriving":[5],"twodimensional":[6],"spectrotemporal":[7,91],"features":[8],"phoneme":[10,23],"recognition":[11],"that":[12],"are":[13,63],"estimated":[14],"to":[15,37,46],"maximize":[16],"the":[17,20,28,39,43,52,59,82,86,89],"separation":[18],"between":[19],"representations":[21],"of":[22,27,42,54,61,88],"classes.":[24],"The":[25],"linearity":[26],"filters":[29,62],"results":[30],"in":[31],"their":[32],"intuitive":[33],"interpretation":[34],"enabling":[35],"us":[36],"investigate":[38],"working":[40],"principles":[41],"system":[44],"and":[45,69],"improve":[47],"its":[48],"performance":[49],"by":[50],"locating":[51],"sources":[53],"error.":[55],"Two":[56],"estimation":[60],"proposed:":[64],"Regularized":[65],"Least":[66],"Square":[67],"(RLS)":[68],"Modified":[70],"Linear":[71],"Discriminant":[72],"Analysis":[73],"(MLDA).":[74],"Both":[75],"reach":[77],"a":[78],"comparable":[79],"improvement":[80],"over":[81],"baseline":[83],"condition":[84],"demonstrating":[85],"advantage":[87],"filters.":[92]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}