Reverberant speech database for training speech dereverberation algorithms and TTS models
Data CreatorValentini-Botinhao, Cassia
PublisherUniversity of Edinburgh
MetadataShow full item record
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.
DescriptionReverberant 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.
Reverberant speech 48kHz waveforms containing 2 native English speakers with around 400 sentences each (Test set) (151.7Mb)
Reverberant speech 48kHz waveforms containing 28 native English speakers with around 400 sentences each (Train set 1) (2.427Gb)
Reverberant speech 48kHz waveforms containing 56 native English speakers with around 400 sentences each (Train set 2) (4.899Gb)
4 text files describing the conditions under which each audio file was created (underlying speech and reverberant condition) (125.8Kb)
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