97 citations · 172 across the 24 of their papers we have counts for
10 papers · 1 filter
Disentangled Representation Learning for Environment-agnostic Speaker Recognition
KiHyun Nam, Hee-Soo Heo, Jee-weon Jung +1
This work presents a framework based on feature disentanglement to learn speaker embeddings that are robust to environmental variations. Our framework utilises an auto-encoder as a…
Encoder-decoder multimodal speaker change detection
Jee-weon Jung, Soonshin Seo, Hee-Soo Heo +5
The task of speaker change detection (SCD), which detects points where speakers change in an input, is essential for several applications. Several studies solved the SCD task using…
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…
Baseline Systems for the First Spoofing-Aware Speaker Verification Challenge: Score and Embedding Fusion
Hye-jin Shim, Hemlata Tak, Xuechen Liu +12
Deep learning has brought impressive progress in the study of both automatic speaker verification (ASV) and spoofing countermeasures (CM). Although solutions are mutually dependent…