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Found 6 papers, 0 papers with code
A Deep Representation Learning-based Speech Enhancement Method Using Complex Convolution Recurrent Variational Autoencoder
{Compared to our preliminary work, DCCRN-VAE introduces a more sophisticated DCCRN structure and probability distribution for DRL.
LE-SSL-MOS: Self-Supervised Learning MOS Prediction with Listener Enhancement
In this paper, we proposed a novel fusion model for MOS prediction that combines supervised and unsupervised approaches.
Hybrid-Regressive Neural Machine Translation
HRT achieves the state-of-the-art BLEU score of 28. 49 on the WMT En-De task and is at least 1. 5x faster than AT, regardless of batch size and device.
The Royalflush System for VoxCeleb Speaker Recognition Challenge 2022
We adapt the speaker embedding extractor using all source and target domain data in a supervised manner, where it can fully leverage both domain information.
Royalflush Speaker Diarization System for ICASSP 2022 Multi-channel Multi-party Meeting Transcription Challenge
This paper describes the Royalflush speaker diarization system submitted to the Multi-channel Multi-party Meeting Transcription Challenge(M2MeT).
The RoyalFlush System of Speech Recognition for M2MeT Challenge
Firstly, we investigated a set of front-end methods, including multi-channel weighted predicted error (WPE), beamforming, speech separation, speech enhancement and so on, to process training, validation and test sets.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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