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Found 15 papers, 8 papers with code
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.
Investigating Speech Features for Continuous Turn-Taking Prediction Using LSTMs
The continuous predictions represent generalized turn-taking behaviors observed in the training data and can be applied to make decisions that are not just limited to end-of-turn detection.
Multimodal Continuous Turn-Taking Prediction Using Multiscale RNNs
To design spoken dialog systems that can conduct fluid interactions it is desirable to incorporate cues from separate modalities into turn-taking models.
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
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.
Neural Generation of Dialogue Response Timings
The timings of spoken response offsets in human dialogue have been shown to vary based on contextual elements of the dialogue.
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.
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
Deep Multi-Scale Feature Learning for Defocus Blur Estimation
This paper presents an edge-based defocus blur estimation method from a single defocused image.
AV Taris: Online Audio-Visual Speech Recognition
In recent years, Automatic Speech Recognition (ASR) technology has approached human-level performance on conversational speech under relatively clean listening conditions.
Low Resource Species Agnostic Bird Activity Detection
This paper explores low resource classifiers and features for the detection of bird activity, suitable for embedded Automatic Recording Units which are typically deployed for long term remote monitoring of bird populations.
Bioacoustic Event Detection with prototypical networks and data augmentation
This report presents deep learning and data augmentation techniques used by a system entered into the Few-Shot Bioacoustic Event Detection for the DCASE2021 Challenge.
Learnable Acoustic Frontends in Bird Activity Detection
Combining this data with species agnostic bird activity detection systems enables the monitoring of activity levels of bird populations.
Learnable Frontends that do not Learn: Quantifying Sensitivity to Filterbank Initialisation
We show that although performance is overall improved, the filterbanks exhibit strong sensitivity to their initialisation strategy.
RoomReader: A Multimodal Corpus of Online Multiparty Conversational Interactions
The corpus was developed within the wider RoomReader Project to explore multimodal cues of conversational engagement and behavioural aspects of collaborative interaction in online environments.
