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Gemini 3.1 Flash TTS Redefines Expressive AI Speech

Natural language audio tags and multi-speaker dialogue enhance TTS precision and control.

Executive Summary

Gemini 3.1 Flash TTS introduces advanced expressivity via natural language audio tags, offering granular vocal control for multi-speaker dialogue across 70+ languages. Engineers can now build highly localized, nuanced audio experiences.

Technical Breakdown

Audio Tags: Granular Speech Control

Gemini 3.1 Flash TTS introduces a transformative feature called audio tags, allowing natural language control over vocal style, pace, tone, and expression. These tags are embedded inline with text input, making them intuitive to use without the need for an advanced scripting layer. For instance, tags like <style='happy'> or <accent='British'> can dynamically alter speech characteristics mid-sentence or across dialogue, providing developers fine-grained control over speech outputs.

Additionally, developers can apply speaker-level specificity with dedicated Audio Profiles. Each profile allows detailed customization for variables such as tone, pacing, and accent. Profiles can also include dynamic Director’s Notes, enabling characters to adjust their delivery depending on context—essential for applications in storytelling, automated scripts, or intelligent assistants.

Multi-Speaker Dialogue and Scene-Choreography

A groundbreaking innovation is Gemini 3.1’s ability to handle native multi-speaker dialogue. Using scene direction tags, developers can design context-aware conversations that feel natural. Characters created with distinct profiles can dynamically react to one another, ensuring that tonal consistency is preserved across multiple interactions. For example:

Why It Matters

Improves TTS expressivity and control at a technical level, appealing to engineers building immersive AI apps.

Community Discussion

Hacker News discussion

Reddit thread

Source & Attribution

Original article: Gemini 3.1 Flash TTS: the next generation of expressive AI speech

Publisher: DeepMind Blog

This analysis was prepared by NowBind AI from the original article and links back to the primary source.

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