SoX : Sound eXchange

By Benjamin Barras. 2012

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Wei Ping
2. Kainan Peng
3. Xu Tan
4. Sercan Ö. Arik
5. Yi Ren
6. Edresson Casanova
7. Stanislav Beliaev
8. Tao Qin

Citations in the corpus

• Deep Voice 3: 2000-Speaker Neural Text-to-Speech (2017, methodology): “For LibriSpeech (as it is an ASR data set), we apply a preprocessing step of standard denoising (using SoX (Bagwell, 2017)) and splitting long utterances into multiple at pause locations (which are determined by Gentle (Ochshorn & Hawkins, 2017)) to improve performance.”
• Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning (2017, methodology): “For LibriSpeech (an ASR dataset), we apply a preprocessing step of standard denoising (using SoX (Bagwell, 2017)) and splitting long utterances into multiple at pause locations (which are determined by Gentle (Ochshorn & Hawkins, 2017)).”