Score guided audio restoration via generalised coupled tensor factorisation
Generalised coupled tensor factorisation is a recently proposed algorithmic framework for simultaneously estimating tensor factorisation models where several observed tensors can share a set of latent factors. This paper proposes a model in this framework for coupled factorisation of piano spectrogr...
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| creator | Simsekli, U. Yilmaz, Y. K. Cemgil, A. T. |
| description | Generalised coupled tensor factorisation is a recently proposed algorithmic framework for simultaneously estimating tensor factorisation models where several observed tensors can share a set of latent factors. This paper proposes a model in this framework for coupled factorisation of piano spectrograms and piano roll representations to solve audio interpolation and restoration problem. The model incorporates temporal and harmonic information from an approximate musical score (not necessarily belonging to the played piece), and spectral information from isolated piano sounds. The performance of the proposed approach is evaluated on the restoration of classical music pieces where we get about 5dB SNR improvement when 50% of data frames are missing. |
| doi_str_mv | 10.1109/ICASSP.2012.6289134 |
| format | Conference Proceeding |
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The performance of the proposed approach is evaluated on the restoration of classical music pieces where we get about 5dB SNR improvement when 50% of data frames are missing.</description><subject>Acoustic noise</subject><subject>Audio Restoration</subject><subject>Computational modeling</subject><subject>Cost function</subject><subject>Coupled Tensor Factorisation</subject><subject>Equations</subject><subject>Mathematical model</subject><subject>Signal to noise ratio</subject><subject>Tensile stress</subject><issn>1520-6149</issn><issn>2379-190X</issn><isbn>1467300454</isbn><isbn>9781467300452</isbn><isbn>9781467300469</isbn><isbn>1467300446</isbn><isbn>9781467300445</isbn><isbn>1467300462</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1kM1OwzAQhM2fRCh5gl78AgleO_HPEVVQEJVASg_cKtfZVEYhqewEibfHgrKXOew3I80QsgRWAjBz97y6b5q3kjPgpeTagKjOSG6UhkoqwVglzTnJuFCmAMPeL8jN_6OuLkkGNWeFhMpckzzGD5YuWZmQGXlp3BiQHmbfYkvt3PqRBozTGOzkx4F-eUsPOGCwvY-JcON87JNOOMQx0M66hPr4C9-Sq872EfOTLsj28WG7eio2r-vUYFN4UPVUSK06bphCgY477cBwBUJzDh0iq6sWjNzvUaHSNZfOiM6lDbRQHETNlFiQ5V-sR8TdMfhPG753p1nED9FJUkk</recordid><startdate>201203</startdate><enddate>201203</enddate><creator>Simsekli, U.</creator><creator>Yilmaz, Y. 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T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-687f2907e3ec2c8c1927138221fee054d196bbe7e78526c93fc1098372135073</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Acoustic noise</topic><topic>Audio Restoration</topic><topic>Computational modeling</topic><topic>Cost function</topic><topic>Coupled Tensor Factorisation</topic><topic>Equations</topic><topic>Mathematical model</topic><topic>Signal to noise ratio</topic><topic>Tensile stress</topic><toplevel>online_resources</toplevel><creatorcontrib>Simsekli, U.</creatorcontrib><creatorcontrib>Yilmaz, Y. K.</creatorcontrib><creatorcontrib>Cemgil, A. T.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Simsekli, U.</au><au>Yilmaz, Y. K.</au><au>Cemgil, A. 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The model incorporates temporal and harmonic information from an approximate musical score (not necessarily belonging to the played piece), and spectral information from isolated piano sounds. The performance of the proposed approach is evaluated on the restoration of classical music pieces where we get about 5dB SNR improvement when 50% of data frames are missing.</abstract><pub>IEEE</pub><doi>10.1109/ICASSP.2012.6289134</doi><tpages>4</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Acoustic noise Audio Restoration Computational modeling Cost function Coupled Tensor Factorisation Equations Mathematical model Signal to noise ratio Tensile stress |
| title | Score guided audio restoration via generalised coupled tensor factorisation |
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