4 citations · 5 across the 4 of their papers we have counts for
4 papers
Absolute decision corrupts absolutely: conservative online speaker diarisation
Youngki Kwon, Hee-Soo Heo, Bong-Jin Lee +2
Our focus lies in developing an online speaker diarisation framework which demonstrates robust performance across diverse domains. In online speaker diarisation, outputs generated…
High-resolution embedding extractor for speaker diarisation
Hee-Soo Heo, Youngki Kwon, Bong-Jin Lee +2
Speaker embedding extractors significantly influence the performance of clustering-based speaker diarisation systems. Conventionally, only one embedding is extracted from each spee…
Large-scale learning of generalised representations for speaker recognition
Jee-weon Jung, Hee-Soo Heo, Bong-Jin Lee +5
The objective of this work is to develop a speaker recognition model to be used in diverse scenarios. We hypothesise that two components should be adequately configured to build su…
In search of strong embedding extractors for speaker diarisation
Jee-weon Jung, Hee-Soo Heo, Bong-Jin Lee +5
Speaker embedding extractors (EEs), which map input audio to a speaker discriminant latent space, are of paramount importance in speaker diarisation. However, there are several cha…