Problem
Research questions and friction points this paper is trying to address.
Source-Grounded Speech Planning
Pre-Synthesis Decision
Citation Legality
Slot Agreement
Evidence Citations
VoxReason: Listener-Free Evaluation of Source-Grounded Speech Planning Before Synthesis
🤖 AI Summary
本文提出VoxReason方法，用于评估语音合成前基于源记录的语音规划决策是否合理，通过自动验证器检查来确保决策依据的有效性。
📝 Abstract
Expressive speech systems make a decision before any waveform is rendered: how an utterance is delivered. In dialogue agents, narration, and role-conditioned TTS, that hidden planning step sets affect, pitch, energy, rate, pause, emphasis, and stance, yet downstream audio scores rarely reveal whether those choices were licensed by the source record, a source-use failure that occurs before any waveform exists. VoxReason makes that pre-synthesis decision measurable as a listener-free task for source-grounded speech planning. Before synthesis, VoxReason measures whether delivery choices are grounded in cited source records. Systems output a source-cited speaking-plan with evidence citations, and a deterministic verifier checks citation legality, slot agreement, unsupported state, schema validity, and one-cue counterfactual locality. On 1,440 checked source-label cases, shortcut controls show why slot accuracy alone is unsafe: a key-lookup oracle reaches 1.000 plan-slot accuracy on seen keys, while an emotion prior still reaches 0.958 slot accuracy on source-key-disjoint cases without citing intensity or identity. In a separate 100-case learned source-key-disjoint comparison, a 7B locality SFT+CF repair improves plan-slot accuracy/locality from 0.684/0.141 to 0.919/1.000, and removing source records lowers citation-required grounded score by 0.488. Rendered waveform quality remains outside the present evaluation.
Innovation
Methods, ideas, or system contributions that make the work stand out.
source-grounded speech planning
listener-free evaluation
citation legality
slot agreement
counterfactual locality
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