kiyoon
/ ffmpeg_nvidia_conda_install.sh
Last active
May 6, 2025 08:15
Install nvidia accelerated ffmpeg in a conda environment.
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| git clone https://git.videolan.org/git/ffmpeg/nv-codec-headers.git | |
| cd nv-codec-headers | |
| vi Makefile # change the first line to PREFIX = ${CONDA_PREFIX} | |
| make install | |
| cd .. | |
| git clone https://git.ffmpeg.org/ffmpeg.git | |
| cd ffmpeg | |
| git checkout n4.2.2 | |
| conda install nasm |
vadimkantorov
/ ctc_alignment_targets.py
Last active
February 5, 2025 13:21
An implementation of CTC re-formulation via cross-entropy with pseudo-labels, following "A Novel Re-weighting Method for Connectionist Temporal Classification"
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| # CTC vanilla and CTC via crossentropy are equal, and their gradients as well. In this reformulation it's easier to experiment with modifications of CTC. | |
| # References on CTC regularization: | |
| # "A Novel Re-weighting Method for Connectionist Temporal Classification", Li et al, https://arxiv.org/abs/1904.10619 | |
| # "Focal CTC Loss for Chinese Optical Character Recognition on Unbalanced Datasets", Feng et al, https://www.hindawi.com/journals/complexity/2019/9345861/ | |
| # "Improved training for online end-to-end speech recognition systems", Kim et al, https://arxiv.org/abs/1711.02212 | |
| import torch | |
| import torch.nn.functional as F | |
| ## generate example data |