Noisy reverberant speech database for training speech enhancement algorithms and TTS models
Data CreatorValentini-Botinhao, Cassia
PublisherUniversity of Edinburgh
MetadataShow full item record
CitationValentini-Botinhao, Cassia. (2017). Noisy reverberant speech database for training speech enhancement algorithms and TTS models, 2016 [dataset]. University of Edinburgh. http://dx.doi.org/10.7488/ds/2139.
DescriptionNoisy reverberant speech database. The database was designed to train and test speech enhancement (noise suppression and dereverberation) methods that operate at 48kHz. Clean speech was made reverberant and noisy by convolving it with a room impulse response and then adding it to a noisy signal that was also convolved 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: http://dx.doi.org/10.7488/ds/2117 .
Noisy reverberant speech 48kHz waveforms of 2 native English speakers with around 400 sentences each (Test set) (168.6Mb)
Noisy reverberant speech 48kHz waveforms of 28 native English speakers with around 400 sentences each (Train set 1) (2.716Gb)
Noisy reverberant speech 48kHz waveforms of 56 native English speakers with around 400 sentences each (Train set 2) (5.498Gb)