CEAEval is a context-aware evaluation system for speech expressive appropriateness, supported by a new Mandarin dataset with multi-dimensional human annotations and a model that outperforms prior systems.
InICASSP 2021-2021 IEEE International Confer- ence on Acoustics, Speech and Signal Processing (ICASSP), pages 6493–6497
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MINT-Bench is a new benchmark using hierarchical taxonomy, multi-stage data pipeline, and hybrid evaluation to assess instruction-following TTS systems, revealing major gaps in compositional and paralinguistic controls.
Appropriateness of TTS varies independently across domains while naturalness scores penalize stylized speech and reward spontaneity.
citing papers explorer
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Evaluating the Expressive Appropriateness of Speech in Rich Contexts
CEAEval is a context-aware evaluation system for speech expressive appropriateness, supported by a new Mandarin dataset with multi-dimensional human annotations and a model that outperforms prior systems.
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MINT-Bench: A Comprehensive Multilingual Benchmark for Instruction-Following Text-to-Speech
MINT-Bench is a new benchmark using hierarchical taxonomy, multi-stage data pipeline, and hybrid evaluation to assess instruction-following TTS systems, revealing major gaps in compositional and paralinguistic controls.
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Is Natural Always Appropriate? Investigating Naturalness and Appropriateness Across Different Domains for TTS Evaluation
Appropriateness of TTS varies independently across domains while naturalness scores penalize stylized speech and reward spontaneity.