Awesome
TSM
Matlab Implementations of Time-Scale Modification
Documentation
Time-Scale Modification Implementations
Stereo Time-Scale Modification
Frequency Dependent Time-Scale Modification
Time-Scale Modification Dataset with Subjective Labels
An Objective Measure of Quality for Time-Scale Modification of Audio
Software Requirements
- MATLAB 2017a or newer.
- Python 3.6
- Pytorch 1.3.1
Citations
This repository covers multiple published papers. Please use the following references when citing this work.
[1] T. Roberts and K.K. Paliwal, (2018) "Stereo Time-Scale Modification Using Sum and Difference Transformation," In 2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS). IEEE. https://doi.org/10.1109/icspcs.2018.8631776.
[2] T. Roberts and K.K. Paliwal, (2018) "Frequency Dependent Time-Scale Modification," In 2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS). IEEE. https://doi.org/10.1109/icspcs.2018.8631764.
[3] T. Roberts and K.K. Paliwal, (2019) "Time-Scale Modification Using Fuzzy Epoch-Synchronous Overlap-Add (FESOLA)," In 2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) (pp. 31-34). IEEE. https://doi.org/10.1109/waspaa.2019.8937258.
[4] T. Roberts and K.K. Paliwal (2020). "A Time-Scale Modification Dataset with Subjective Quality Labels," in J. Acoust. Soc. Am., 148(1), pp. 201-210.https://doi.org/10.1121/10.0001567.
[5] T. Roberts, "A Time-Scale Modification Dataset with Subjective Quality Labels", IEEE Dataport, 2020. [Online]. Available: http://dx.doi.org/10.21227/ny9p-rv41. Accessed: Jul. 15, 2020.
[6] T. Roberts and K.K. Paliwal (2021). "An Objective Measure of Quality for Time-Scale Modification of Audio," in J. Acoust. Soc. Am., 149(3), pp. 1843-1854. Available: https://doi.org/10.1121/10.0003753
[7] T. Roberts, A. Nicolson and K.K. Paliwal (2021). "Deep Learning-Based Single-Ended Quality Prediction for Time-Scale Modified Audio," in J. Audio Eng. Soc., 69(9), pp. 644-655. Available: https://doi.org/10.17743/jaes.2021.0031