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Funderdc.contributor.otherEPSRC - Engineering and Physical Sciences Research Councilen_UK
Spatial Coveragedc.coverage.spatialUNITED KINGDOMen_UK
Spatial Coveragedc.coverage.spatialUKen_UK
Time Perioddc.coverage.temporalstart=2016-01; end=2016-06; scheme=W3C-DTF
Time Perioddc.coverage.temporalstart=2016-01; end=2016-06; scheme=W3C-DTFen
Data Creatordc.creatorValentini-Botinhao, Cassia
Date Accessioneddc.date.accessioned2017-08-21T11:03:20Z
Date Availabledc.date.available2017-08-21T11:03:20Z
Citationdc.identifier.citationValentini-Botinhao, Cassia. (2017). Noisy speech database for training speech enhancement algorithms and TTS models, 2016 [sound]. University of Edinburgh. School of Informatics. Centre for Speech Technology Research (CSTR). https://doi.org/10.7488/ds/2117.en
Persistent Identifierdc.identifier.urihttp://hdl.handle.net/10283/2791
Persistent Identifierdc.identifier.urihttps://doi.org/10.7488/ds/2117
Dataset Description (abstract)dc.description.abstractClean and noisy parallel speech database. The database was designed to train and test speech enhancement methods that operate at 48kHz. A more detailed description can be found in the papers associated with the database. For the 28 speaker dataset, details can be found in: C. Valentini-Botinhao, X. Wang, S. Takaki & J. Yamagishi, "Speech Enhancement for a Noise-Robust Text-to-Speech Synthesis System using Deep Recurrent Neural Networks", In Proc. Interspeech 2016. For the 56 speaker dataset: C. Valentini-Botinhao, X. Wang, S. Takaki & J. Yamagishi, "Investigating RNN-based speech enhancement methods for noise-robust Text-to-Speech”, In Proc. SSW 2016. Some of the noises used to create the noisy speech were obtained from the Demand database, available here: http://parole.loria.fr/DEMAND/ . The speech database was obtained from the CSTR VCTK Corpus, available here: https://doi.org/10.7488/ds/1994. The speech-shaped and babble noise files that were used to create this dataset are available here: http://homepages.inf.ed.ac.uk/cvbotinh/se/noises/.en_UK
Languagedc.language.isoengen_UK
Publisherdc.publisherUniversity of Edinburgh. School of Informatics. Centre for Speech Technology Research (CSTR)en_UK
Relation (Is Referenced By)dc.relation.isreferencedbyhttp://www.research.ed.ac.uk/portal/en/publications/speech-enhancement-for-a-noiserobust-texttospeech-synthesis-system-using-deep-recurrent-neural-networks(08deb6fd-79c0-490f-ae46-f37034b6bfb4).htmlen_UK
Relation (Is Referenced By)dc.relation.isreferencedbyValentini Botinhao, C, Wang, X, Takaki, S and Yamagishi, J 2016, Speech Enhancement for a Noise-Robust Text-to-Speech Synthesis System using Deep Recurrent Neural Networks. in Proceedings of Interspeech 2016. pp. 352-356. DOI: 10.21437/Interspeech.2016-159en_UK
Relation (Is Referenced By)dc.relation.isreferencedbyhttps://doi.org/10.1109/TASLP.2018.2828980
Relation (Is Referenced By)dc.relation.isreferencedbyCassia Valentini-Botinhao ; Junichi Yamagishi. Speech Enhancement of Noisy and Reverberant Speech for Text-to-Speech. IEEE/ACM Transactions on Audio, Speech, and Language Processing ( Volume: 26, Issue: 8, Aug. 2018 ) .https://doi.org/10.1109/TASLP.2018.2828980.
Supersedesdc.relation.replaceshttp://datashare.is.ed.ac.uk/handle/10283/1942en_UK
Rightsdc.rightsCreative Commons Attribution 4.0 International Public Licenseen
Sourcedc.sourcehttp://parole.loria.fr/DEMAND/en_UK
Sourcedc.sourceThe CSTR VCTK Corpus (https://doi.org/10.7488/ds/1994)
Subjectdc.subjectnoisy speechen_UK
Subjectdc.subjectspeech enhancementen_UK
Subjectdc.subjectspeech synthesisen_UK
Subjectdc.subjectVCTKen_UK
Subject Classificationdc.subject.classificationMathematical and Computer Sciences::Speech and Natural Language Processingen_UK
Titledc.titleNoisy speech database for training speech enhancement algorithms and TTS modelsen_UK
Typedc.typesounden_UK

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