AffectCodec is an emotion-guided neural speech codec that preserves emotional cues during quantization while maintaining semantic fidelity and prosodic naturalness.
EMO-SUPERB: An In-Depth Look at Speech Emotion Recognition
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 2
citation-polarity summary
roles
background 2polarities
background 2representative citing papers
Speech-FT applies drift-reduced fine-tuning followed by weight-space interpolation to improve both task performance and cross-task generalization in models such as HuBERT and WavLM.
citing papers explorer
-
AffectCodec: Emotion-Preserving Neural Speech Codec for Expressive Speech Modeling
AffectCodec is an emotion-guided neural speech codec that preserves emotional cues during quantization while maintaining semantic fidelity and prosodic naturalness.
-
Speech-FT: Merging Pre-trained And Fine-Tuned Speech Representation Models For Cross-Task Generalization
Speech-FT applies drift-reduced fine-tuning followed by weight-space interpolation to improve both task performance and cross-task generalization in models such as HuBERT and WavLM.
- Toward Fair Speech Technologies: A Comprehensive Survey of Bias and Fairness in Speech AI