Felix Weninger
Felix Weninger is a senior tech lead (Senior Principal Research Scientist) at Nuance Communications. His research interests include deep learning, speech recognition, speech emotion recognition, and source separation. He received his PhD degree in computer science from Technical University of Munich (TUM), Germany, in 2015. Prior to joining Nuance, he worked at Mitsubishi Electric Research Labs (MERL), Cambridge, MA, USA and in the Machine Intelligence and Signal Processing Group at TUM's Institute for Human-Machine Communication. He has published more than 100 peer-reviewed papers in books, journals, and conference proceedings.
Felix Weninger’s stories
Combining the advantages of close-talk and far-talk speech recognition

Transcribing conversations between doctor and patients, as in Nuance’s Dragon Ambient eXperience (DAX) solution, is a very challenging application for speech recognition. One reason is that today’s speech recognition systems can reach optimal performance only for close-talk input, which requires the speaker to wear a headset microphone or use a handheld device like a mobile […]

Reducing the human labeling effort for training end-to-end speech recognition

Deep learning technology has rapidly transformed the way that computers perform speech recognition. It has enabled us to build speech recognizers for very challenging applications such as Dragon Ambient eXperience (DAX), which transcribes conversations between doctor and patient. In particular, the end-to-end (E2E) speech recognition system has been a primary focus of research in recent […]

Delivering personalized user experiences with speaker adapted end-to-end speech recognition

A crucial capability of automatic speech recognition (ASR) systems is to cope with variability in speech, caused by various accents, age groups, or other variations in speaking style, as well as noisy environments. Several years ago, Nuance’s Dragon dictation product line pioneered the usage of deep learning technology for speaker adaptation in professional dictation systems. […]