Moshi AI vs Altered Studio

Moshi AI is a speech-native conversational model from Kyutai, a Paris-based open-science research lab. Instead of chaining speech recognition, text generation, and text-to-speech, Moshi processes audio directly and holds full-duplex voice conversations with minimal latency.

Its multi-stream design runs separate channels for the user, Moshi's spoken output, and an Inner Monologue text stream that improves coherence. That setup lets Moshi listen and talk at the same time, handle overlaps, interruptions, and backchanneling like a real conversation rather than rigid speaker turns.

Moshi is built on Helium, a 7B language model, and Mimi, Kyutai's neural audio codec. Weights and inference code ship for PyTorch, Rust, and MLX, and you can try it in the browser at moshi-chat.kyutai.org. Researchers, voice AI developers, and anyone building real-time spoken interfaces will find the most value here.

Altered Studio morphs recorded or live speech into curated or custom voices for media production and real-time calls. Its speech-to-speech engine runs in the browser or locally on Windows and Mac, with a separate Real-Time Pro app for gaming, call centers, and voice restoration during video calls.

Most voice changers trade quality for latency or the reverse. Altered splits the stack: media production morphing targets recording quality on GPUs with post-edit refinements, while Real-Time Pro uses 1 to 4 CPU cores for low-latency skins, accent translation, and Euphonia support for dysphonia and disfluencies.

Podcasters, game studios, and call-center teams use it to dub multi-character scenes, swap accents on live calls, and clean noisy dialogue. The Studio page offers transcription in 75+ languages, translation, and text-to-speech voice-over in 70+ languages from major providers in one editor.