Fundamental Frequency (and higher harmonics) waveform extraction from continuous speech using Empirical Mode Decomposition (EMD). The code was used to obtained fundamental waveforms for modelling the auditory brainstem responses to continous speech in [1-4].

Method was originally developed in [1] and this repository serves for code maintenece, so please do feel free to report issues or suggest improvements.

• For best results use mono float .wav files sampled at 44100 Hz.
• If you come across a bug or any sort of unexpected behaviour, please open an issue on GitHub.

• [1] Forte, A. E., Etard, O., & Reichenbach, T. (2017). The human auditory brainstem response to running speech reveals a subcortical mechanism for selective attention. Elife, 6, e27203. https://doi.org/10.7554/eLife.27203
• [2] Etard, O.*, Kegler, M.*, Braiman, C., Forte, A. E., & Reichenbach, T. (2019). Decoding of selective attention to continuous speech from the human auditory brainstem response. Neuroimage, 200, 1-11. https://doi.org/10.1016/j.neuroimage.2019.06.029
• [3] Saiz-Alia, M., Forte, A. E., & Reichenbach, T. (2019). Individual differences in the attentional modulation of the human auditory brainstem response to speech inform on speech-in-noise deficits. Scientific reports, 9(1), 1-10. https://doi.org/10.1038/s41598-019-50773-1
• [4] Saiz-Alia, M., & Reichenbach, T. (2020). Computational modeling of the auditory brainstem response to continuous speech. Journal of Neural Engineering. https://doi.org/10.1088/1741-2552/ab970d