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Found 5 papers, 1 papers with code
Joint Training or Not: An Exploration of Pre-trained Speech Models in Audio-Visual Speaker Diarization
The scarcity of labeled audio-visual datasets is a constraint for training superior audio-visual speaker diarization systems.
Wespeaker baselines for VoxSRC2023
This report showcases the results achieved using the wespeaker toolkit for the VoxSRC2023 Challenge.
A Multi-task Multi-stage Transitional Training Framework for Neural Chat Translation
To address these issues, in this paper, we propose a multi-task multi-stage transitional (MMT) training framework, where an NCT model is trained using the bilingual chat translation dataset and additional monolingual dialogues.
Confidence Based Bidirectional Global Context Aware Training Framework for Neural Machine Translation
Most dominant neural machine translation (NMT) models are restricted to make predictions only according to the local context of preceding words in a left-to-right manner.
Asynchronous Bidirectional Decoding for Neural Machine Translation
The dominant neural machine translation (NMT) models apply unified attentional encoder-decoder neural networks for translation.
