update default (#94)

README.md

@@ -11,8 +11,10 @@ The starter project includes:
 - A simple voice AI assistant, ready for extension and customization
 - A voice AI pipeline built on [LiveKit Inference](https://docs.livekit.io/agents/models/inference), providing zero-configuration access to [models](https://docs.livekit.io/agents/models) from top labs
   - Uses the fast, open-weight Gemma 4 31B model, [hosted by LiveKit](https://docs.livekit.io/agents/models/llm/livekit/) and tuned for optimal performance in voice AI, as the default LLM
+  - Uses Fish Audio S2.1 Pro for TTS, which renders the inline delivery markup that expressive mode relies on
   - Supports more than 50 models from OpenAI, Cartesia, Deepgram, and other providers
   - Access to a wide range of other models, including [Realtime models](https://docs.livekit.io/agents/models/realtime), through extensive plugin ecosystem
+- Expressive mode, enabled by default: the framework injects the TTS provider's markup guide into the LLM prompt, so the model emits inline delivery tags (emotion, pacing, non-verbal sounds) that the TTS renders and the transcript never shows
 - Eval suite based on the LiveKit Agents [testing & evaluation framework](https://docs.livekit.io/agents/start/testing/)
 - [LiveKit Turn Detector](https://docs.livekit.io/agents/logic/turns/turn-detector/), an end-of-turn model that listens to the user's audio directly, combining semantic understanding with acoustic cues for state-of-the-art accuracy across 14 languages
 - [Background voice cancellation](https://docs.livekit.io/transport/media/noise-cancellation/)