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Found 4 papers, 2 papers with code
SPADE: Self-supervised Pretraining for Acoustic DisEntanglement
Self-supervised representation learning approaches have grown in popularity due to the ability to train models on large amounts of unlabeled data and have demonstrated success in diverse fields such as natural language processing, computer vision, and speech.
Challenges and Opportunities in Multi-device Speech Processing
We review current solutions and technical challenges for automatic speech recognition, keyword spotting, device arbitration, speech enhancement, and source localization in multidevice home environments to provide context for the INTERSPEECH 2022 special session, "Challenges and opportunities for signal processing and machine learning for multiple smart devices".
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Interspeech 2021 Deep Noise Suppression Challenge
In this version of the challenge organized at INTERSPEECH 2021, we are expanding both our training and test datasets to accommodate full band scenarios.
Massively Parallel Methods for Deep Reinforcement Learning
We present the first massively distributed architecture for deep reinforcement learning.
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