The successful candidate will contribute to an EPSRC project “SpeechWave” which aims to develop methods for robust speech recognition. SpeechWave is a collaborative project between the University of Edinburgh and King’s College London, with partners that include the University of California, Berkeley, SRI International, Menlo Park, California, the BBC, and two SMEs.
The successful candidates will play a leading role in the development of speech recognition systems that work over a wide range of adverse environments, including high levels of noise and reverberation. A key aspect of the work will be a focus on approaches that operate directly in the domain of acoustic waveforms or some high dimensional representation of speech. The posts will include the development of acoustic models using recurrent neural networks (RNNs), deep kernel structures, and/or representations such as Deep Scattering Spectrum.
The role is expected to involve working with state-of-the-art and novel acoustic and language modelling methods and architectures for end-to-end learning. The post will also offer the opportunity for annual extended visits to the Department of Statistics, UC Berkeley and to the Speech Laboratory, SRI International, Menlo Park.
- Cutting edge research in the project area as specified in the above.
- Publication and dissemination of research results.
The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.