Speaker augmentation via resampling and rescaling creates pseudo-speakers and hard training samples that reduce target confusion and improve end-to-end speaker extraction.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.SD 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
An Investigation on Speaker Augmentation for End-to-End Speaker Extraction
Speaker augmentation via resampling and rescaling creates pseudo-speakers and hard training samples that reduce target confusion and improve end-to-end speaker extraction.