Dessa
Dessa is Block's speech-to-speech artificial intelligence model for conversational voice research and applications. It takes audio input and produces audio output directly, without converting speech into text as an intermediate step. Trained from scratch on human conversation rather than text, the model supports full-duplex interaction, listening and speaking at the same time, and runs locally on a MacBook Pro with an M4 Max chip or better. It captures conversational cues such as emotion, sarcasm, laughter, pauses, and turn-taking that can be lost in text-based pipelines. Dessa is intended for AI safety researchers and developers studying voice-model behavior, privacy, and real-time interaction. It is a speech model for research and development, not a general-purpose business application or hosted voice-agent platform.
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Cartesia Sonic-3.6
Sonic is a real-time text-to-speech model built for voice agents, combining natural delivery, sub-90ms latency, and native support for more than 40 languages. It is designed to make voice interactions feel effortless, with tone that adjusts to context, consistent pacing, and speech that follows the natural rhythm of conversation. By default, Sonic interprets the emotional subtext of a transcript and calibrates delivery automatically, while non-verbal expressions such as laughter can be inserted directly into the text. The model follows transcripts faithfully, produces clean audio across languages and voices, and handles alphanumeric content such as order numbers, phone numbers, IDs, and email addresses naturally without preprocessing. Context-aware pronunciation helps heteronyms sound correct from surrounding words, while custom pronunciation dictionaries let teams define how proper nouns and domain-specific terms should be spoken.
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MAI-Voice-2.1
MAI-Voice-2.1 is Microsoft's hosted text-to-speech model for developers building voice-enabled products. It generates expressive speech from text, supports multilingual output across 23 languages, and offers emotion and style controls, long-form speaker consistency, and gated matching to consented reference voices. Developers access it through Microsoft Foundry and Azure Speech APIs and SDKs for narration, audiobooks, voice assistants, and customer-service experiences.
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Higgs Realtime
Higgs Realtime is a production-quality, real-time speech-to-speech model and API built for natural, continuous conversation. It is an end-to-end, instruction-tuned, audio-native model that can understand audio, text, or both and generate high-quality responses, while also functioning as a text LLM when given text alone. Designed for live voice agents, it follows conversations, handles interruptions, adapts when requests change mid-sentence, and carries multi-step workflows through to completion. The model is trained specifically for voice-agent reflexes such as natural turn-taking, conversational cadence, tone adaptation, spoken tool preambles, multi-turn state tracking, and robust instruction following through changing requests. Semantic turn detection helps distinguish a completed turn from a pause, while multilingual and code-switched understanding supports more than 100 languages without per-language setup.
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