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Found 9 papers, 4 papers with code
An Empirical Study of Topic Transition in Dialogue
Transitioning between topics is a natural component of human-human dialog.
Learning to Count Words in Fluent Speech enables Online Speech Recognition
Sequence to Sequence models, in particular the Transformer, achieve state of the art results in Automatic Speech Recognition.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Should we hard-code the recurrence concept or learn it instead ? Exploring the Transformer architecture for Audio-Visual Speech Recognition
The audio-visual speech fusion strategy AV Align has shown significant performance improvements in audio-visual speech recognition (AVSR) on the challenging LRS2 dataset.
How to Teach DNNs to Pay Attention to the Visual Modality in Speech Recognition
A recently proposed multimodal fusion strategy, AV Align, based on state-of-the-art sequence to sequence neural networks, attempts to model this relationship by explicitly aligning the acoustic and visual representations of speech.
Attention-based Audio-Visual Fusion for Robust Automatic Speech Recognition
Automatic speech recognition can potentially benefit from the lip motion patterns, complementing acoustic speech to improve the overall recognition performance, particularly in noise.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Just Talking - Modelling Casual Conversation
Casual conversation has become a focus for artificial dialogue applications.
Can DNNs Learn to Lipread Full Sentences?
Finding visual features and suitable models for lipreading tasks that are more complex than a well-constrained vocabulary has proven challenging.
