AffectCodec is an emotion-guided neural speech codec that preserves emotional cues during quantization while maintaining semantic fidelity and prosodic naturalness.
arXiv preprint arXiv:2402.13018 , year=
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The paper delivers a unified framework for fairness in speech technologies by formalizing seven definitions, organizing research into three paradigms, diagnosing pipeline-specific biases, and mapping mitigations to those sources.
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
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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.
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Toward Fair Speech Technologies: A Comprehensive Survey of Bias and Fairness in Speech AI
The paper delivers a unified framework for fairness in speech technologies by formalizing seven definitions, organizing research into three paradigms, diagnosing pipeline-specific biases, and mapping mitigations to those sources.
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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.