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.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
eess.AS 2years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
AnyAudio-Judge introduces a rubric-based benchmark with 7920 samples and a trained evaluator model using SFT and GRPO on 105K CoT samples to assess and enhance instruction following in audio generation.
citing papers explorer
-
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.
-
AnyAudio-Judge: A Dynamic Rubric-Based Benchmark and Evaluator for Audio Instruction Following
AnyAudio-Judge introduces a rubric-based benchmark with 7920 samples and a trained evaluator model using SFT and GRPO on 105K CoT samples to assess and enhance instruction following in audio generation.