Introduces CCG-CFG with inconsistency-based dynamic scales and hard-sample mining distillation to boost emotional alignment in auto-regressive TTS, reporting up to 12% absolute gains in emotion recognition accuracy.
Less annotating, more classify- ing – addressing the data scarcity issue of supervised machine learning with deep transfer learning and bert - nli,
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Cross-modal Consistency Guidance for Robust Emotion Control in Auto-Regressive TTS Models
Introduces CCG-CFG with inconsistency-based dynamic scales and hard-sample mining distillation to boost emotional alignment in auto-regressive TTS, reporting up to 12% absolute gains in emotion recognition accuracy.