Reverberant speech database for training speech dereverberation algorithms and TTS models

Valentini-Botinhao, Cassia

Depositor	dc.contributor	Valentini-Botinhao, Cassia
Funder	dc.contributor.other	EPSRC - Engineering and Physical Sciences Research Council	en_UK
Spatial Coverage	dc.coverage.spatial	UK	en
Spatial Coverage	dc.coverage.spatial	UNITED KINGDOM	en
Time Period	dc.coverage.temporal	start=2016-05; end=2016-06; scheme=W3C-DTF	en
Data Creator	dc.creator	Valentini-Botinhao, Cassia
Date Accessioned	dc.date.accessioned	2016-06-10T15:50:09Z
Date Available	dc.date.available	2016-06-10T15:50:09Z
Citation	dc.identifier.citation	Valentini-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 Identifier	dc.identifier.uri	https://hdl.handle.net/10283/2031
Persistent Identifier	dc.identifier.uri	https://doi.org/10.7488/ds/1425
Dataset Description (abstract)	dc.description.abstract	Reverberant 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.tableofcontents	The 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
Language	dc.language.iso	eng	en_UK
Publisher	dc.publisher	University of Edinburgh	en_UK
Relation (Is Version Of)	dc.relation.isversionof	The 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.isreferencedby	Cassia 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.isreferencedby	https://doi.org/10.1109/TASLP.2018.2828980
Relation (Is Referenced By)	dc.relation.isreferencedby	Cassia 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.
Rights	dc.rights	Creative Commons Attribution 4.0 International Public License	en
Source	dc.source	The ACE challenge (http://www.commsp.ee.ic.ac.uk/~sap/projects/ace-challenge/)
Source	dc.source	The MIRD database (http://www.iks.rwth-aachen.de/en/research/tools-downloads/multichannel-impulse-response-database/)
Source	dc.source	The MARDY database (http://www.commsp.ee.ic.ac.uk/~sap/resources/mardy-multichannel-acoustic-reverberation-database-at-york-database/)
Source	dc.source	The CSTR VCTK Corpus (https://doi.org/10.7488/ds/1994)
Subject	dc.subject	reverberant speech	en_UK
Subject	dc.subject	speech dereverberation	en_UK
Subject	dc.subject	speech synthesis	en_UK
Subject	dc.subject	Voice Bank Corpus	en_UK
Subject	dc.subject	ACE dataset	en_UK
Subject	dc.subject	MIRD dataset	en_UK
Subject	dc.subject	MARDY dataset	en_UK
Subject Classification	dc.subject.classification	Mathematical and Computer Sciences::Speech and Natural Language Processing	en_UK
Title	dc.title	Reverberant speech database for training speech dereverberation algorithms and TTS models	en_UK
Type	dc.type	dataset	en_UK