Toshiba Cambridge Research Laboratory
Cambridge Research Laboratory > Speech Technology

Speech Technology

The Speech Technology Group (STG) is at the heart of modern artificial intelligence by designing novel algorithms for automatic speech recognition and data-based dialogue systems enabling the creation of advanced and natural, speech enabled, human-machine interfaces.

In that context, our target is to create new products and services that facilitate the access of information and the creation of knowledge effectively, for improving productivity and quality of life.

STG has made significant contributions to the next generation of Toshiba’s speech recognition and HMM-based speech synthesis. In addition to core underlying technology, the STG has developed speech technology for the major North American and European languages. We work in collaboration with the speech R&D groups at the Knowledge Media Lab, Toshiba RDC, Kawasaki, Japan and Toshiba China R&D Center, Beijing, China, and business divisions of Toshiba Group, Japan.

Working with groups within Toshiba, we have a tight coupling between our R&D efforts and current and future product development. This enables us to ensure that our research work will be of direct practical benefit. We fund research and have academic collaborations with groups in various UK and European Union Universities and Research Centers. Combining the strengths of our group with these collaborations, we address various research topics for the future.

More about STG

Latest Publications

Subband Temporal Envelope Features and Data Augmentation for End-To-End Recognition of Distant Conversational Speech
C.T. Do
Proc. IEEE ICASSP 2019, Brighton, UK, May 2019
An Unsupervised Learning Approach to Neutral-Net-Supported WPE Dereverberation
P. Petkov, V. Tsiaras, R. Doddipatla and Y. Stylianou
Proc. IEEE ICASSP 2019, Brighton, UK, May 2019
On Reducing the Effect of Speaker Overlap for CHiME-5
T.C. Zorila and R. Doddipatla
Proc. IEEE ICASSP 2019, Brighton, UK, May 2019
Prediction of Dialogue Success with Spectral and Rhythm Acoustic Features using DNNs and SVMs
A. Lykartsis, M. Kotti, A. Papangelis and Y. Stylianou
Proc. IEEE Spoken Language Technology Workshop (SLT) 2018, Athens, Greece, December 2018
Comparison of an End-To-End Trainable Dialogue System with a Modular Statistical Dialogue System
N. Braunschweiler and A. Papangelis
Proc. Interspeech 2018, Hyderabad, India, September 2018

More STG publications

To Top