We would like to thank applicants for putting the time and effort into creating GSoC applications to work on CMUSphinx. We were ultimately provided with two slots and had many great applications that made choosing very difficult. We hope that students who were not accepted will still get involved with CMUSphinx and look forward to receiving your applications next year.
We are pleased to announce that two spots were awarded to Michal Krajňanský and Apurv Tiwari.
Michal is a student at Masaryk University in Brno, Czech Republic. He is taking Informatics - Artificial Intelligence & Natural Language Processing. Michal will be working on training acoustic models on long audio files. This will be done by optimizing SphinxTrain through the utilization of massively parallel hardware - the NVIDIA CUDA framework. It will enable acoustic model training on long audio files by the utilization of the NVIDIA CUDA architecture that will reduce the memory requirements of the Baum-Welch algorithm and significantly speed things up. Lastly, he will also modify SphinxTrain to be able to process long input audio files.
Apurv is a student at the Indian Institute of Technology Delhi in New Delhi, India. He is taking Mathematics and Computing. Apurv will be working on adding Long Audio Alignment to CMUSphinx. The problem he will solve is to align a given approximate-transcription for audio data corresponding to the audio file as well as improve the transcription at points of low confidence.
Both Apurv and Michal will blog weekly about their experience. The blogs will appear here at https://cmusphinx.github.io/
We want to thank Google for providing this wonderful opportunity and the mentors for donating their valuable time. We eagerly anticipate great things from Apurv and Michal. Stay tuned!