3 ms·

Please please please someone please share an IPython notebook with something working already :)

ThePhysicist 10y ago
I have some iPython notebooks for speech analysis using a Chinese corpus. I used those for a tutorial on machine learning with Python and unfortunately they are still a bit incomplete, but maybe you find them useful nevertheless (no deep learning involved though). What I do in the tutorial is to start from a WAV file and then go through all the steps required for analyzing the data (using a "traditional" approach), i.e. generate the Mel-Cepstrum coefficients of the segmented audio data and then train a model to distinguish individual words. Word segmentation is another topic that I touch a bit, and where we can also use machine learning to improve the results. Here's a version with very simple speech training data (basically just different syllables with different tones): https://github.com/adewes/machine-learning-chinese/blob/master/training/part_3/Chinese%20Speech%20Recognition.ipynb https://github.com/adewes/machine-learning-chinese/blob/mast... More complex speech training data (from a real-world Chinese speech corpus [not included but downloadable]): https://github.com/adewes/machine-learning-chinese/blob/master/training/part_3/old/Chinese%20Speech%20Recognition.ipynb https://github.com/adewes/machine-learning-chinese/blob/mast... There are other parts of the tutorial that deal with Chinese text and character recognition as well, if you're interested: https://github.com/adewes/machine-learning-chinese https://github.com/adewes/machine-learning-chinese For part 2 I also train a simple neural network with lasagne (a Python library for deep learning), and I plan to add more deep learning content and do a clean write-up of the whole thing as soon as I have some more time.
- ronreiter 10y ago
  Thanks! will take a look.
novalis78 10y ago
I second that!
deleted 10y ago
[deleted]
visarga 10y ago
It takes 90 minutes to synthesize 1 second. Sorry, no laptop version yet. https://twitter.com/hardmaru/status/773968758519902208 https://twitter.com/hardmaru/status/773968758519902208

I have some iPython notebooks for speech analysis using a Chinese corpus. I used those for a tutorial on machine learning with Python and unfortunately they are still a bit incomplete, but maybe you find them useful nevertheless (no deep learning involved though). What I do in the tutorial is to start from a WAV file and then go through all the steps required for analyzing the data (using a "traditional" approach), i.e. generate the Mel-Cepstrum coefficients of the segmented audio data and then train a model to distinguish individual words. Word segmentation is another topic that I touch a bit, and where we can also use machine learning to improve the results. Here's a version with very simple speech training data (basically just different syllables with different tones): https://github.com/adewes/machine-learning-chinese/blob/master/training/part_3/Chinese%20Speech%20Recognition.ipynb https://github.com/adewes/machine-learning-chinese/blob/mast... More complex speech training data (from a real-world Chinese speech corpus [not included but downloadable]): https://github.com/adewes/machine-learning-chinese/blob/master/training/part_3/old/Chinese%20Speech%20Recognition.ipynb https://github.com/adewes/machine-learning-chinese/blob/mast... There are other parts of the tutorial that deal with Chinese text and character recognition as well, if you're interested: https://github.com/adewes/machine-learning-chinese https://github.com/adewes/machine-learning-chinese For part 2 I also train a simple neural network with lasagne (a Python library for deep learning), and I plan to add more deep learning content and do a clean write-up of the whole thing as soon as I have some more time.

ronreiter 10y ago
Thanks! will take a look.

novalis78 10y ago

I second that!

deleted 10y ago

[deleted]

visarga 10y ago

It takes 90 minutes to synthesize 1 second. Sorry, no laptop version yet. https://twitter.com/hardmaru/status/773968758519902208 https://twitter.com/hardmaru/status/773968758519902208