Filtering model training method and speech recognition method
A filtering model training method includes obtaining N original syllables, obtaining N recognized syllables, and obtaining N syllable distances based on the N original syllables and the N recognized syllables, where the N syllable distances are in a one-to-one correspondence with N syllable pairs, t...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Patent |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | Nie, Weiran Yu, Hai |
| description | A filtering model training method includes obtaining N original syllables, obtaining N recognized syllables, and obtaining N syllable distances based on the N original syllables and the N recognized syllables, where the N syllable distances are in a one-to-one correspondence with N syllable pairs, the N original syllables and the N recognized syllables form the N syllable pairs, each syllable pair includes an original syllable and a recognized syllable that correspond to each other, and each syllable distance is used to indicate a similarity between an original syllable and a recognized syllable that are included in a corresponding syllable pair. |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US11211052B2</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US11211052B2</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US11211052B23</originalsourceid><addsrcrecordid>eNrjZLB1y8wpSS3KzEtXyM1PSc1RKClKzMwDc1NLMvJTFBLzUhSKC1JTkzMUilKT89PzMksy8_OgsjwMrGmJOcWpvFCam0HRzTXE2UM3tSA_PrW4IDE5NS-1JD402NDQyNDQwNTIyciYGDUAOpMwcQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Filtering model training method and speech recognition method</title><source>esp@cenet</source><creator>Nie, Weiran ; Yu, Hai</creator><creatorcontrib>Nie, Weiran ; Yu, Hai</creatorcontrib><description>A filtering model training method includes obtaining N original syllables, obtaining N recognized syllables, and obtaining N syllable distances based on the N original syllables and the N recognized syllables, where the N syllable distances are in a one-to-one correspondence with N syllable pairs, the N original syllables and the N recognized syllables form the N syllable pairs, each syllable pair includes an original syllable and a recognized syllable that correspond to each other, and each syllable distance is used to indicate a similarity between an original syllable and a recognized syllable that are included in a corresponding syllable pair.</description><language>eng</language><subject>ACOUSTICS ; MUSICAL INSTRUMENTS ; PHYSICS ; SPEECH ANALYSIS OR SYNTHESIS ; SPEECH OR AUDIO CODING OR DECODING ; SPEECH OR VOICE PROCESSING ; SPEECH RECOGNITION</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20211228&DB=EPODOC&CC=US&NR=11211052B2$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76289</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20211228&DB=EPODOC&CC=US&NR=11211052B2$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Nie, Weiran</creatorcontrib><creatorcontrib>Yu, Hai</creatorcontrib><title>Filtering model training method and speech recognition method</title><description>A filtering model training method includes obtaining N original syllables, obtaining N recognized syllables, and obtaining N syllable distances based on the N original syllables and the N recognized syllables, where the N syllable distances are in a one-to-one correspondence with N syllable pairs, the N original syllables and the N recognized syllables form the N syllable pairs, each syllable pair includes an original syllable and a recognized syllable that correspond to each other, and each syllable distance is used to indicate a similarity between an original syllable and a recognized syllable that are included in a corresponding syllable pair.</description><subject>ACOUSTICS</subject><subject>MUSICAL INSTRUMENTS</subject><subject>PHYSICS</subject><subject>SPEECH ANALYSIS OR SYNTHESIS</subject><subject>SPEECH OR AUDIO CODING OR DECODING</subject><subject>SPEECH OR VOICE PROCESSING</subject><subject>SPEECH RECOGNITION</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2021</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZLB1y8wpSS3KzEtXyM1PSc1RKClKzMwDc1NLMvJTFBLzUhSKC1JTkzMUilKT89PzMksy8_OgsjwMrGmJOcWpvFCam0HRzTXE2UM3tSA_PrW4IDE5NS-1JD402NDQyNDQwNTIyciYGDUAOpMwcQ</recordid><startdate>20211228</startdate><enddate>20211228</enddate><creator>Nie, Weiran</creator><creator>Yu, Hai</creator><scope>EVB</scope></search><sort><creationdate>20211228</creationdate><title>Filtering model training method and speech recognition method</title><author>Nie, Weiran ; Yu, Hai</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US11211052B23</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2021</creationdate><topic>ACOUSTICS</topic><topic>MUSICAL INSTRUMENTS</topic><topic>PHYSICS</topic><topic>SPEECH ANALYSIS OR SYNTHESIS</topic><topic>SPEECH OR AUDIO CODING OR DECODING</topic><topic>SPEECH OR VOICE PROCESSING</topic><topic>SPEECH RECOGNITION</topic><toplevel>online_resources</toplevel><creatorcontrib>Nie, Weiran</creatorcontrib><creatorcontrib>Yu, Hai</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Nie, Weiran</au><au>Yu, Hai</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Filtering model training method and speech recognition method</title><date>2021-12-28</date><risdate>2021</risdate><abstract>A filtering model training method includes obtaining N original syllables, obtaining N recognized syllables, and obtaining N syllable distances based on the N original syllables and the N recognized syllables, where the N syllable distances are in a one-to-one correspondence with N syllable pairs, the N original syllables and the N recognized syllables form the N syllable pairs, each syllable pair includes an original syllable and a recognized syllable that correspond to each other, and each syllable distance is used to indicate a similarity between an original syllable and a recognized syllable that are included in a corresponding syllable pair.</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_epo_espacenet_US11211052B2 |
| source | esp@cenet |
| subjects | ACOUSTICS MUSICAL INSTRUMENTS PHYSICS SPEECH ANALYSIS OR SYNTHESIS SPEECH OR AUDIO CODING OR DECODING SPEECH OR VOICE PROCESSING SPEECH RECOGNITION |
| title | Filtering model training method and speech recognition method |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-09T19%3A34%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=Nie,%20Weiran&rft.date=2021-12-28&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS11211052B2%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |