arXiv (All)
open access
Continuous-Time Acoustic Modelling with Neural Controlled Differential Equations
Text-to-speech (TTS) models commonly address text--speech alignment by expanding phone-level encoder states to frame-level decoder inputs using predicted durations. While this length-regulation step resolves alignment structurally, this use of duration typically changes only where and how often late
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- UniVoice: Unifying Autoregressive ASR and Flow-Matching based TTS with Large Language Models#927171
- Interpreting and Evaluating Dynamic-Rate Speech Codec Boundaries#1132152
- FuseAlign: Forced Alignment in the Wild#1118723
- Mask, Sample, Revise: A Revisable CTMC Inference Stack for Guided Discrete Flow Matching Text-to-Speech#1084253
- CTC-TTS: LLM-based dual-streaming text-to-speech with CTC alignment#984119
Record · ID 999415
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive