Thank you to all of the contributors who have keept CMUSphinx alive over the last decade, in particular to Nickolay Shmyrev and the whole team at Alpha Cephei. As you may have noticed, active development has mostly ceased over the last few years, and the technological foundation of CMUSphinx has become quite antiquated.
For state-of-the-art speech recognition the Alpha Cephei team is now working exclusively on Vosk, and there are a number of other open source options, notably Coqui, wav2vec, Julius, TensorFlowASR, DeepSpeech and of course Kaldi.
Nonetheless, there are still many people using CMUSphinx and PocketSphinx in particular, so there is some value in maintaining (if not actually developing) it. Its users frequently encounter difficulties due to the build system, which could be corrected by modernizing the codebase slightly. Due to the eternal "pre-alpha" status of the system, there are also many problems of portability and stability that should be adressed.
For this reason, we are preparing a true release of PocketSphinx, with a focus on a modern build system with no external dependencies, and a stable, documented, and easy to use API in C and Python. In addition, SphinxTrain will either continue to be maintained or will simply be integrated into PocketSphinx.
Finally, SourceForge is no longer a viable option for hosting. From now on, the GitHub Project is the official home of CMUSphinx, and we will soon migrate all the other downloads (models, etc) and close the SourceForge site.
Dear users, you've might been asking yourself why there were not so many updates on CMUSphinx recently. Time goes really fast and many things change in ASR. Deep learning, huge NLP models like BERT, Tacotron and Wavenet/Waveglow/WaveRNN, Pytorch vs Tensorflow, huge datsets, chatbots and so on and so forth. Many new toolkits appear and some disappear - Eesen, Espresso, Kaldi, Wav2letter, NeMo. The whole area is thriving.
CMUSphinx team has been actively participating in all those activities, creating new models, applications, helping newcomers and showing the best way to implement speech recognition system. We are here to suggest you the easiest way to start such an exciting world of speech recognition. Lately we implemented a Kaldi on Android, providing much better accuracy for large vocabulary decoding, which was hard to imagine before.
If you are interested in learning more, check Alpha Cephei website, our Github and join us on Telegram and Reddit.
Stay tuned!
Hi everyone! My name’s Sahith Dambekodi and I’m a second year undergrad student at BITS Pilani K.K. Birla Goa Campus. I’m pursuing a major in Electrical and Electronics engineering. This is my blog for Google Summer of Code 2017!
The list of accepted projects for Google Summer of Code 2017 has been announced today. Please check
There are two major parts, one is pronunciation evaluation, we have several sub-projects about it, another part is about deep neural networks in pocketsphinx. Hopefully, the accuracy of our decoders will improve significantly. An interesting project is dedicated to more tight ROS integration, hopefully using speech recognition in robots will be way easier soon.
Congratulations to accepted students! Great summer ahead, lots of fun it seems.