背景与半正式指令
Speech editing for content creation requires precise control over both what an edit should do and where it should apply. Free-form natural language provides a flexible interface for expressing edit requests, but its ambiguity may leave the intended operation, parameters, or target region underspecified. We study a semi-formal transcript-grounded edit instruction that specifies operation categories and parameters and binds them to transcript spans or boundaries. This semantic timeline avoids explicit timestamp alignment and provides an externally inspectable contract for compositional edits.
模型实例
We instantiate the interface in dots$.$tts$.$edit, a speech editing model built on a continuous autoregressive speech generation architecture.
四类语音创作控制
- Lexical content（文本编辑）
- Affective expression（情感表达）
- Pitch and speaking-rate delivery（音高与语速传递）
- Temporal phrasing（时间短语编辑）
通过 text、emotion、prosody 和 pause editing 实现。
数据管道
Task-specific data pipelines construct operation- and scope-controlled pairs while retaining source-derived context outside each target region.
双语基准 doteBench
We further introduce doteBench, a bilingual benchmark that measures precise instruction following, local preservation, and audio quality across the four controls and their composition.
实验结果
Experiments show leading overall instruction following and local preservation across its five editing categories, while audio quality remains comparable to existing open-source systems. Across three Seed-TTS-Eval shards, the model shows negligible differences from the base model in zero-shot TTS recognition error rate and speaker similarity.