Comments (1)
jzlianglu
commented on May 20, 2024
Hi @yotam319, thanks a lot for your advice and code sample. Yes, what you said definitely makes sense. Previously, I only did a vanilla version of LF-MMI in the toolbox, and planed to revisit later to improve the efficiency. I noticed the code change in the pykaldi lib, but have not been able to squeeze my time to work on it. Our internal tools are not built on Kaldi, so I have very limited time to work on this toolkit. Will try to integrate your dataloader into the code base soon. Thanks again!
from pykaldi2.
Related Issues (14)
- Why negative grad_input of LF_MMI loss? HOT 1
- How to use CE regularizer in chain-model training? HOT 1
- Why is the chain loss computation so slow? HOT 8
- RIR format
- Problems about HCLG.fst needed by "train_transformer_se.py" HOT 2
- SETraining is extremely slow HOT 4
- Decoding with train_transformer_ce.py HOT 2
- no module named 'kaldi.base._kaldi_error'
- Physical data format
- Selective data simulation
- Targeted simulation
- incompatible pytorch and torchvision version HOT 1
- Convolve vs. BlockConvolve for RIR Augmentation HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from pykaldi2.