#Voice

AIMeta's Muse Realtime Avatar was rated ahead of two leading commercial avatar systems in live-call products, based on 2–3 minute conversations with matched avatar identities. Raters compared visual quality, sync, character consistency, and mannerisms, and Muse Realtime Avatar came out ahead on overall preference.

AIMeta's Muse Realtime Voice generates speech tokens encoding both content and prosody, and Muse Realtime Avatar consumes that shared stream to produce streaming video. Using a fixed-length history as motion context keeps computation bounded regardless of conversation length while synchronizing voice, lip motion, and expressions.

AIThinking Machines Lab announced a research preview of interaction models that take in audio, video, and text continuously and respond in real time without external turn-detection harnesses. The model, TML-Interaction-Small, is a 276B-parameter MoE with 12B active parameters, paired with an asynchronous background model for sustained reasoning and tool use. The post reports competitive intelligence scores and lower turn-taking latency against GPT-realtime and Gemini Live models, along with new interactivity benchmarks where baseline models largely failed.

Why it matters: The post explains a time-aligned, full-duplex design and benchmarks against turn-based models, showing how interaction and background reasoning can be split across two cooperating models.