Show simple item record

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
Citationdc.identifier.citationValentini-Botinhao, Cassia. (2016). Reverberant speech database for training speech dereverberation algorithms and TTS models, 2016 [dataset]. University of Edinburgh.
Persistent Identifierdc.identifier.uri
Persistent Identifierdc.identifier.uri
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 (; - The MIRD database (; - The MARDY database ( The underlying clean speech data can be found in:
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
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).
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.isreferencedby
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 ) .
Rightsdc.rightsCreative Commons Attribution 4.0 International Public Licenseen
Sourcedc.sourceThe ACE challenge (
Sourcedc.sourceThe MIRD database (
Sourcedc.sourceThe MARDY database (
Sourcedc.sourceThe CSTR VCTK Corpus (
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

Download All
zip file MD5 Checksum: c62255bbabeccbba8ea4b57be36c6f94

Files in this item


This item appears in the following Collection(s)

Show simple item record