Borderless Long Speech Synthesis
Most existing text-to-speech (TTS) systems either synthesize speech sentence by sentence and stitch the results together, or drive synthesis from plain-text dialogues alone. Both approaches leave models with little understanding of global context or paralinguistic cues, making it hard to capture real-world phenomena such as multi-speaker interactions (interruptions, overlapping speech), evolving emotional arcs, and varied acoustic environments. We introduce the Borderless Long Speech Synthesis framework for agent-centric, borderless long audio synthesis. Rather than targeting a single narrow task, the system is designed as a unified capability set spanning VoiceDesigner, multi-speaker syn...
| Authors | Xingchen Song, Di Wu, Dinghao Zhou et al. |
|---|---|
| Primary category | cs.SD |
| Published | 20 March 2026 |
| Last updated at source | 3 April 2026 |
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