2 citations · 2 across the 3 of their papers we have counts for
5 papers
Pushing the Limits of End-to-End Diarization
Samuel J. Broughton, Lahiru Samarakoon
In this paper, we present state-of-the-art diarization error rates (DERs) on multiple publicly available datasets, including AliMeeting-far, AliMeeting-near, AMI-Mix, AMI-SDM, DIHA…
Configurable Multilingual ASR with Speech Summary Representations
Harrison Zhu, Ivan Fung, Yingke Zhu +1
Approximately half of the world's population is multilingual, making multilingual ASR (MASR) essential. Deploying multiple monolingual models is challenging when the ground-truth l…
EEND-M2F: Masked-attention mask transformers for speaker diarization
Marc Härkönen, Samuel J. Broughton, Lahiru Samarakoon
In this paper, we make the explicit connection between image segmentation methods and end-to-end diarization methods. From these insights, we propose a novel, fully end-to-end diar…
Robust End-to-End Diarization with Domain Adaptive Training and Multi-Task Learning
Ivan Fung, Lahiru Samarakoon, Samuel J. Broughton
Due to the scarcity of publicly available diarization data, the model performance can be improved by training a single model with data from different domains. In this work, we prop…
Transformer Attractors for Robust and Efficient End-to-End Neural Diarization
Lahiru Samarakoon, Samuel J. Broughton, Marc Härkönen +1
End-to-end neural diarization with encoder-decoder based attractors (EEND-EDA) is a method to perform diarization in a single neural network. EDA handles the diarization of a flexi…