137 citations · 558 across the 32 of their papers we have counts for
42 papers
Towards Robust Waveform-Based Acoustic Models
Dino Oglic, Zoran Cvetkovic, Peter Sollich +2
We study the problem of learning robust acoustic models in adverse environments, characterized by a significant mismatch between training and test conditions. This problem is of pa…
Automatic audiovisual synchronisation for ultrasound tongue imaging
Aciel Eshky, Joanne Cleland, Manuel Sam Ribeiro +3
Ultrasound tongue imaging is used to visualise the intra-oral articulators during speech production. It is utilised in a range of applications, including speech and language therap…
Silent versus modal multi-speaker speech recognition from ultrasound and video
Manuel Sam Ribeiro, Aciel Eshky, Korin Richmond +1
We investigate multi-speaker speech recognition from ultrasound images of the tongue and video images of the lips. We train our systems on imaging data from modal speech, and evalu…
Exploiting ultrasound tongue imaging for the automatic detection of speech articulation errors
Manuel Sam Ribeiro, Joanne Cleland, Aciel Eshky +2
Speech sound disorders are a common communication impairment in childhood. Because speech disorders can negatively affect the lives and the development of children, clinical interv…
Train your classifier first: Cascade Neural Networks Training from upper layers to lower layers
Shucong Zhang, Cong-Thanh Do, Rama Doddipatla +3
Although the lower layers of a deep neural network learn features which are transferable across datasets, these layers are not transferable within the same dataset. That is, in gen…
TaL: a synchronised multi-speaker corpus of ultrasound tongue imaging, audio, and lip videos
Manuel Sam Ribeiro, Jennifer Sanger, Jing-Xuan Zhang +4
We present the Tongue and Lips corpus (TaL), a multi-speaker corpus of audio, ultrasound tongue imaging, and lip videos. TaL consists of two parts: TaL1 is a set of six recording s…