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09/02/2023
eDKM: An Efficient and Accurate Train-time Weight Clustering for Large Language Models
Since Large Language Models or LLMs have demonstrated high-quality perfo...
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05/20/2023
Efficient Multimodal Neural Networks for Trigger-less Voice Assistants
The adoption of multimodal interactions by Voice Assistants (VAs) is gro...
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05/18/2023
PDP: Parameter-free Differentiable Pruning is All You Need
DNN pruning is a popular way to reduce the size of a model, improve the ...
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03/14/2023
R^2: Range Regularization for Model Compression and Quantization
Model parameter regularization is a widely used technique to improve gen...
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04/05/2022
Improving Voice Trigger Detection with Metric Learning
Voice trigger detection is an important task, which enables activating a...
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03/30/2022
Device-Directed Speech Detection: Regularization via Distillation for Weakly-Supervised Models
We address the problem of detecting speech directed to a device that doe...
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08/28/2021
DKM: Differentiable K-Means Clustering Layer for Neural Network Compression
Deep neural network (DNN) model compression for efficient on-device infe...
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05/14/2021
Streaming Transformer for Hardware Efficient Voice Trigger Detection and False Trigger Mitigation
We present a unified and hardware efficient architecture for two stage v...
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08/05/2020
Hybrid Transformer/CTC Networks for Hardware Efficient Voice Triggering
We consider the design of two-pass voice trigger detection systems. We f...
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01/25/2020
Lattice-based Improvements for Voice Triggering Using Graph Neural Networks
Voice-triggered smart assistants often rely on detection of a trigger-ph...
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12/07/2018
Nonlinear Conjugate Gradients For Scaling Synchronous Distributed DNN Training
Nonlinear conjugate gradient (NLCG) based optimizers have shown superior...
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10/31/2018
