DATA DRIVEN AUDIO ENHANCEMENT
Systems and methods are disclosed for audio enhancement. For example, methods may include accessing audio data; determining a window of audio samples based on the audio data; inputting the window of audio samples to a classifier to obtain a classification, in which the classifier includes a neural n...
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 | Casas, Raul Alejandro Rowen, Christopher Mao, Xuehong Maydan, Dror Wojcicki, Kamil Krzysztof Hijazi, Samer |
| description | Systems and methods are disclosed for audio enhancement. For example, methods may include accessing audio data; determining a window of audio samples based on the audio data; inputting the window of audio samples to a classifier to obtain a classification, in which the classifier includes a neural network and the classification takes a value from a set of multiple classes of audio; selecting, based on the classification, an audio enhancement network from a set of multiple audio enhancement networks; applying the selected audio enhancement network to the window of audio samples to obtain an enhanced audio segment, in which the selected audio enhancement network includes a neural network that has been trained using audio signals of a type associated with the classification; and storing, playing, or transmitting an enhanced audio signal based on the enhanced audio segment. |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2024371392A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2024371392A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2024371392A13</originalsourceid><addsrcrecordid>eNrjZJB1cQxxVHAJ8gxz9VNwDHXx9Fdw9fNw9HN29XX1C-FhYE1LzClO5YXS3AzKbq4hzh66qQX58anFBYnJqXmpJfGhwUYGRibG5obGlkaOhsbEqQIAAPkh1A</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>DATA DRIVEN AUDIO ENHANCEMENT</title><source>esp@cenet</source><creator>Casas, Raul Alejandro ; Rowen, Christopher ; Mao, Xuehong ; Maydan, Dror ; Wojcicki, Kamil Krzysztof ; Hijazi, Samer</creator><creatorcontrib>Casas, Raul Alejandro ; Rowen, Christopher ; Mao, Xuehong ; Maydan, Dror ; Wojcicki, Kamil Krzysztof ; Hijazi, Samer</creatorcontrib><description>Systems and methods are disclosed for audio enhancement. For example, methods may include accessing audio data; determining a window of audio samples based on the audio data; inputting the window of audio samples to a classifier to obtain a classification, in which the classifier includes a neural network and the classification takes a value from a set of multiple classes of audio; selecting, based on the classification, an audio enhancement network from a set of multiple audio enhancement networks; applying the selected audio enhancement network to the window of audio samples to obtain an enhanced audio segment, in which the selected audio enhancement network includes a neural network that has been trained using audio signals of a type associated with the classification; and storing, playing, or transmitting an enhanced audio signal based on the enhanced audio segment.</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>2024</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=20241107&DB=EPODOC&CC=US&NR=2024371392A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,309,782,887,25571,76555</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20241107&DB=EPODOC&CC=US&NR=2024371392A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Casas, Raul Alejandro</creatorcontrib><creatorcontrib>Rowen, Christopher</creatorcontrib><creatorcontrib>Mao, Xuehong</creatorcontrib><creatorcontrib>Maydan, Dror</creatorcontrib><creatorcontrib>Wojcicki, Kamil Krzysztof</creatorcontrib><creatorcontrib>Hijazi, Samer</creatorcontrib><title>DATA DRIVEN AUDIO ENHANCEMENT</title><description>Systems and methods are disclosed for audio enhancement. For example, methods may include accessing audio data; determining a window of audio samples based on the audio data; inputting the window of audio samples to a classifier to obtain a classification, in which the classifier includes a neural network and the classification takes a value from a set of multiple classes of audio; selecting, based on the classification, an audio enhancement network from a set of multiple audio enhancement networks; applying the selected audio enhancement network to the window of audio samples to obtain an enhanced audio segment, in which the selected audio enhancement network includes a neural network that has been trained using audio signals of a type associated with the classification; and storing, playing, or transmitting an enhanced audio signal based on the enhanced audio segment.</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>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZJB1cQxxVHAJ8gxz9VNwDHXx9Fdw9fNw9HN29XX1C-FhYE1LzClO5YXS3AzKbq4hzh66qQX58anFBYnJqXmpJfGhwUYGRibG5obGlkaOhsbEqQIAAPkh1A</recordid><startdate>20241107</startdate><enddate>20241107</enddate><creator>Casas, Raul Alejandro</creator><creator>Rowen, Christopher</creator><creator>Mao, Xuehong</creator><creator>Maydan, Dror</creator><creator>Wojcicki, Kamil Krzysztof</creator><creator>Hijazi, Samer</creator><scope>EVB</scope></search><sort><creationdate>20241107</creationdate><title>DATA DRIVEN AUDIO ENHANCEMENT</title><author>Casas, Raul Alejandro ; Rowen, Christopher ; Mao, Xuehong ; Maydan, Dror ; Wojcicki, Kamil Krzysztof ; Hijazi, Samer</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2024371392A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2024</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>Casas, Raul Alejandro</creatorcontrib><creatorcontrib>Rowen, Christopher</creatorcontrib><creatorcontrib>Mao, Xuehong</creatorcontrib><creatorcontrib>Maydan, Dror</creatorcontrib><creatorcontrib>Wojcicki, Kamil Krzysztof</creatorcontrib><creatorcontrib>Hijazi, Samer</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Casas, Raul Alejandro</au><au>Rowen, Christopher</au><au>Mao, Xuehong</au><au>Maydan, Dror</au><au>Wojcicki, Kamil Krzysztof</au><au>Hijazi, Samer</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>DATA DRIVEN AUDIO ENHANCEMENT</title><date>2024-11-07</date><risdate>2024</risdate><abstract>Systems and methods are disclosed for audio enhancement. For example, methods may include accessing audio data; determining a window of audio samples based on the audio data; inputting the window of audio samples to a classifier to obtain a classification, in which the classifier includes a neural network and the classification takes a value from a set of multiple classes of audio; selecting, based on the classification, an audio enhancement network from a set of multiple audio enhancement networks; applying the selected audio enhancement network to the window of audio samples to obtain an enhanced audio segment, in which the selected audio enhancement network includes a neural network that has been trained using audio signals of a type associated with the classification; and storing, playing, or transmitting an enhanced audio signal based on the enhanced audio segment.</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_epo_espacenet_US2024371392A1 |
| 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 | DATA DRIVEN AUDIO ENHANCEMENT |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-04T23%3A47%3A19IST&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=Casas,%20Raul%20Alejandro&rft.date=2024-11-07&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2024371392A1%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 |