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05/17/2022
Deploying self-supervised learning in the wild for hybrid automatic speech recognition
Self-supervised learning (SSL) methods have proven to be very successful...
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12/10/2021
Sequence-level self-learning with multiple hypotheses
In this work, we develop new self-learning techniques with an attention-...
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12/10/2021
Building a great multi-lingual teacher with sparsely-gated mixture of experts for speech recognition
The sparsely-gated Mixture of Experts (MoE) can magnify a network capaci...
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10/19/2021
Tackling Dynamics in Federated Incremental Learning with Variational Embedding Rehearsal
Federated Learning is a fast growing area of ML where the training datas...
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10/15/2021
Multilingual Speech Recognition using Knowledge Transfer across Learning Processes
Multilingual end-to-end(E2E) models have shown a great potential in the ...
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06/14/2021
Dynamic Gradient Aggregation for Federated Domain Adaptation
In this paper, a new learning algorithm for Federated Learning (FL) is i...
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01/19/2021
UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data
In this paper, we propose a unified pre-training approach called UniSpee...
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08/06/2020
Federated Transfer Learning with Dynamic Gradient Aggregation
In this paper, a Federated Learning (FL) simulation platform is introduc...
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02/06/2020
Robust Multi-channel Speech Recognition using Frequency Aligned Network
Conventional speech enhancement technique such as beamforming has known ...
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02/01/2020
Fully Learnable Front-End for Multi-Channel Acoustic Modeling using Semi-Supervised Learning
In this work, we investigated the teacher-student training paradigm to t...
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03/13/2019
Multi-Geometry Spatial Acoustic Modeling for Distant Speech Recognition
The use of spatial information with multiple microphones can improve far...
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03/13/2019
Frequency Domain Multi-channel Acoustic Modeling for Distant Speech Recognition
Conventional far-field automatic speech recognition (ASR) systems typica...
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01/05/2019
