2 citations · 2 across the 6 of their papers we have counts for
3 papers · 1 filter
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…
Improving End-to-End Neural Diarization Using Conversational Summary Representations
Samuel J. Broughton, Lahiru Samarakoon
Speaker diarization is a task concerned with partitioning an audio recording by speaker identity. End-to-end neural diarization with encoder-decoder based attractor calculation (EE…