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Depositordc.contributorValentini-Botinhao, Cassia
Funderdc.contributor.otherEPSRC - Engineering and Physical Sciences Research Councilen_UK
Spatial Coveragedc.coverage.spatialUKen
Spatial Coveragedc.coverage.spatialUNITED KINGDOMen
Time Perioddc.coverage.temporalstart=2016-05; end=2016-06; scheme=W3C-DTFen
Data Creatordc.creatorValentini-Botinhao, Cassia
Date Accessioneddc.date.accessioned2016-06-10T15:50:09Z
Date Availabledc.date.available2016-06-10T15:50:09Z
Citationdc.identifier.citationValentini-Botinhao, Cassia. (2016). Reverberant speech database for training speech dereverberation algorithms and TTS models, 2016 [dataset]. University of Edinburgh. https://doi.org/10.7488/ds/1425.en
Persistent Identifierdc.identifier.urihttps://hdl.handle.net/10283/2031
Persistent Identifierdc.identifier.urihttps://doi.org/10.7488/ds/1425
Dataset Description (abstract)dc.description.abstractReverberant speech database. The database was designed to train and test speech dereverberation methods that operate at 48kHz. Clean speech was made reverberant by convolving it with a room impulse response. The room impulse responses used to create this dataset were selected from: - The ACE challenge (http://www.commsp.ee.ic.ac.uk/~sap/projects/ace-challenge/); - The MIRD database (http://www.iks.rwth-aachen.de/en/research/tools-downloads/multichannel-impulse-response-database/); - The MARDY database (http://www.commsp.ee.ic.ac.uk/~sap/resources/mardy-multichannel-acoustic-reverberation-database-at-york-database/). The underlying clean speech data can be found in: https://doi.org/10.7488/ds/2117.en_UK
Dataset Description (TOC)dc.description.tableofcontentsThe files are wav format audio data sampled at 48kHz. Each file contains a sentence recorded by a range of speakers in quiet studio conditions. This audio material was convolved with a range of different room impulse responses, constituting the parallel reverberant dataset. Accompanying each audio file there is a text file containing the orthographic transcription of what was said in that particular audio sample.en_UK
Languagedc.language.isoengen_UK
Publisherdc.publisherUniversity of Edinburghen_UK
Relation (Is Version Of)dc.relation.isversionofThe clean speech version of this dataset and the orthographic transcription of each sentence can be found as: Valentini-Botinhao, Cassia. (2016). Noisy speech database for training speech enhancement algorithms and TTS models, [dataset]. University of Edinburgh. School of Informatics. Centre for Speech Technology Research (CSTR). https://doi.org/10.7488/ds/1356.en_UK
Relation (Is Referenced By)dc.relation.isreferencedbyCassia Valentini-Botinhao, Xin Wang, Shinji Takaki and Junichi Yamagishi. 2016. "Speech Enhancement for a Noise-Robust Text-to-Speech Synthesis System using Deep Recurrent Neural Networks" in Interspeech 2016.
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.
Rightsdc.rightsCreative Commons Attribution 4.0 International Public Licenseen
Sourcedc.sourceThe ACE challenge (http://www.commsp.ee.ic.ac.uk/~sap/projects/ace-challenge/)
Sourcedc.sourceThe MIRD database (http://www.iks.rwth-aachen.de/en/research/tools-downloads/multichannel-impulse-response-database/)
Sourcedc.sourceThe MARDY database (http://www.commsp.ee.ic.ac.uk/~sap/resources/mardy-multichannel-acoustic-reverberation-database-at-york-database/)
Sourcedc.sourceThe CSTR VCTK Corpus (https://doi.org/10.7488/ds/1994)
Subjectdc.subjectreverberant speechen_UK
Subjectdc.subjectspeech dereverberationen_UK
Subjectdc.subjectspeech synthesisen_UK
Subjectdc.subjectVoice Bank Corpusen_UK
Subjectdc.subjectACE dataseten_UK
Subjectdc.subjectMIRD dataseten_UK
Subjectdc.subjectMARDY dataseten_UK
Subject Classificationdc.subject.classificationMathematical and Computer Sciences::Speech and Natural Language Processingen_UK
Titledc.titleReverberant speech database for training speech dereverberation algorithms and TTS modelsen_UK
Typedc.typedataseten_UK

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