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Found 7 papers, 0 papers with code
An Efficient and Streaming Audio Visual Active Speaker Detection System
This paper delves into the challenging task of Active Speaker Detection (ASD), where the system needs to determine in real-time whether a person is speaking or not in a series of video frames.
Active Speaker Detection
Audio-Visual Active Speaker Detection
RepCNN: Micro-sized, Mighty Models for Wakeword Detection
Always-on machine learning models require a very low memory and compute footprint.
Streaming Anchor Loss: Augmenting Supervision with Temporal Significance
Streaming neural network models for fast frame-wise responses to various speech and sensory signals are widely adopted on resource-constrained platforms.
R2 Loss: Range Restriction Loss for Model Compression and Quantization
To overcome the challenge, we focus on outliers in weights of a pre-trained model which disrupt effective lower bit quantization and compression.
Ranked #1 on
Model Compression
on QNLI
HEiMDaL: Highly Efficient Method for Detection and Localization of wake-words
Streaming keyword spotting is a widely used solution for activating voice assistants.
Ranked #1 on
Keyword Spotting
on hey Siri
I see what you hear: a vision-inspired method to localize words
This paper explores the possibility of using visual object detection techniques for word localization in speech data.
Optimize what matters: Training DNN-HMM Keyword Spotting Model Using End Metric
The DNN, in prior methods, is trained independent of the HMM parameters to minimize the cross-entropy loss between the predicted and the ground-truth state probabilities.
Ranked #2 on
Keyword Spotting
on hey Siri
