#3 CMU Sphinx

Hello all!

Time is passing and we are closer and closer to the end of the “Summer of code”.

Here is my progress since I previously posted:

- I implemented a module the clusters the gaussians from a mean file into a given number of classes. The clustering is made considering the euclidean distance between them. The purpose of clustering is to optimize adaptation process.

- I also implemented a module that adapts the acoustic model using the clustering tool that I’ve just described. The main idea of this type of adapting is the following: for each class(cluster) we collect counts separately and generate a separate transform. This way a more particular transform is estimated for each gaussian.

You can see my work at:

- https://github.com/bogdanpetcu/sphinx4/tree/master/sphinx4-core/src/main/java/edu/cmu/sphinx/decoder/adaptation        - adaptation package that I implemented from scratch.

- https://github.com/bogdanpetcu/sphinx4/tree/master/sphinx4-core/src/main/java/edu/cmu/sphinx/decoder/adaptation/clustered        - clustered adaptation package that I implemented from scratch.

- https://github.com/bogdanpetcu/sphinx4/commits/master        - here you can see all of my commits


Enjoy the rest of your summer!

Bogdan Constantin Petcu


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