Block Unveils Dessa: A Full-Duplex Speech Model Trained Entirely on Speech Data

Block has released Dessa, a full-duplex speech model that was trained exclusively on raw speech data without text transcriptions or intermediate representations, enabling simultaneous bidirectional audio conversation rather than the turn-taking approach of most current voice models. Full-duplex capability means the model can listen and speak at the same time, handling interruptions, backchannels, and overlapping speech in a way that closely mirrors natural human conversation dynamics. For developers building voice agents, this is architecturally significant — most deployed voice systems today introduce latency and awkwardness by enforcing strict speaker turns. Dessa's speech-only training approach also suggests a path to voice models that are less dependent on high-quality text-audio paired datasets. Block's entry into frontier speech modeling is unexpected and worth evaluating alongside existing offerings from ElevenLabs, OpenAI, and AssemblyAI.