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Noisy reverberant speech database for training speech enhancement algorithms and TTS models

  • Cassia Valentini Botinhao (Creator)

Dataset

Abstract

Noisy 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.

Data Citation

Valentini-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.
Date made available14 Sept 2017
PublisherEdinburgh DataShare

  • Speech Enhancement of Noisy and Reverberant Speech for Text-to-Speech

    Valentini Botinhao, C. & Yamagishi, J., 1 Aug 2018, In: IEEE/ACM Transactions on Audio, Speech and Language Processing. 26, 8, p. 1420-1433 14 p.

    Research output: Contribution to journal › Article › peer-review

    Open Access
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