Active research for theoretical and applied topics of speech technology and smart interactions. Regarding deep learning besides the basic architectures (feed-forward, convolution, recurrent - LSTM, GRU) we study autoencoders, synthetic gradients and other emerging topics. Additonal topics include text processing, time series classification and prediction. Our colleague - Bálint Gyires-Tóth- has been an accredited trainer and academic ambassador of the NVidia Deep Learning Institute.
The Lab has developed the following technologies and applications:
- multiple speech synthesis technologies on several computer plaforms (Windows, Android, Linux, ...)
- special speech technology applications (e.g. railway announcement system, person and company name synthesis, price list synthesis. Speech synthesis for visually and speech impaired people, communication application for stroke and aphasic patients, call center automation, social robor application, multimodal information system for elderly people)
Recent related EU projects: PAELIFE, VUK, DANSPLAT, AI4EU, APH-ALARM
Tasks in the projects: deep learning algorithms, user interface design, system issues
Project laboratory topics
- Conversational AI applications
- Speech synthesis application for aphasic patients
- Talking mobile applications
- Deep learning – based machine learning
- Silent Speech Interface
- Deep learning based self-driving car methods
- My own radio channel
Description of the lectures