A voice agent has to do more than hear a request and produce a reply. It has to keep the interaction moving while it listens, reasons, uses tools, and speaks. A delay at either end can turn a conversation into a series of awkward pauses.
Today, we’re introducing three new Microsoft AI (MAI) models in Microsoft Foundry:
- MAI-Transcribe-2-Streaming, which turns live speech into text as it arrives
- MAI-Voice-2.1, our most expressive multilingual text-to-speech model yet
- MAI-Voice-2.1-Flash, optimized for responsive, high-volume voice applications.
Together, they give developers more choice in how to build natural voice experiences.
MAI-Transcribe-2-Streaming: Understand speech while it’s happening
Earlier this month, we introduced MAI-Transcribe-2, raising the bar for transcription accuracy, speed, and cost efficiency. It ranked #1 on FLEURS for multilingual accuracy and #1 on the Artificial Analysis accuracy × latency Pareto frontier, giving developers high-quality transcription without trading away speed. With MAI-Transcribe-2-Streaming, we’re extending that leadership to real-time conversations.
Instead of waiting for someone to finish speaking before returning text, MAI-Transcribe-2-Streaming transcribes continuously across 60 languages, with automatic language detection. It produces its first hypotheses, known as partials, within the low hundreds of milliseconds of receiving audio, then refines them as more context arrives and commits a stable transcript once the utterance ends.
That distinction matters when an application needs to act while someone is speaking. A customer-service agent can begin identifying a caller’s request before the sentence is complete. A voice assistant can start reasoning or preparing a tool call sooner. A live transcription experience can surface words almost as quickly as they are spoken.
And the proof is in the results. MAI-Transcribe-2-Streaming debuts at #1 for accuracy on both partial and final transcripts on the Artificial Analysis leaderboard. In most cases, words appear in the transcript as early as 320 milliseconds after they’re spoken, while the closest competition takes more than 500 milliseconds.
Together, MAI-Transcribe-2 and MAI-Transcribe-2-Streaming give developers a choice depending on the experience they’re building:
- MAI-Transcribe-2 for when you need high-quality transcription with capabilities like speaker diarization and word-level timestamps
- MAI-Transcribe-2-Streaming for when your application needs to understand and act on speech as it happens.
MAI-Voice-2.1: One voice across languages
The other half of a voice experience is how it sounds. MAI-Voice-2.1 generates natural, expressive speech across 23 languages, with a consistent voice identity across supported languages.
A tutoring app, for example, can move from an English explanation to a Mandarin exercise without sounding as though a different teacher has taken over. A multilingual assistant can respond in the user’s language while retaining the voice people recognize. The model adapts its pronunciation and delivery to the language rather than carrying one accent across every response.
Choose MAI-Voice-2.1 when voice quality is central to the experience: interactive learning, branded assistants, narration, or content where expression and consistency matter.
MAI-Voice-2.1-Flash: Responsive speech at scale
MAI-Voice-2.1-Flash supports the same languages and cross-language voice identities, but is optimized for workloads where response time and volume are critical. In the supplied comparison, Flash is 55% faster and 60% less expensive than competing models in its class*.
That makes Flash a natural fit for live support agents, voice assistants, and other applications that generate spoken responses throughout the day. Developers can choose MAI-Voice-2.1 when expressive fidelity is the priority, or Flash when they need to balance natural speech with responsiveness and cost at scale.
Put the models to work together
These models really come to life when applied together to build expressive voice agents. Consider a customer calling to change a reservation. MAI-Transcribe-2-Streaming begins returning text while the customer is still speaking. The agent can identify the emerging request, check availability, and prepare an action. Once it has an answer, MAI-Voice-2.1-Flash delivers the response in natural speech. Saving time in listening and speaking gives the agent more room to reason and use tools while keeping the exchange conversational.
Developers can apply the same pattern to:
- Customer-service agents that follow a request as it unfolds, retrieve relevant information, and respond aloud.
- Multilingual assistants that recognize the spoken language and reply in a consistent voice across supported languages.
- Interactive learning experiences that move between languages, speakers, and conversational exercises.
- Live captions and voice-driven interfaces that surface words as they arrive instead of waiting for a completed recording.
Start building
All three models are available in Microsoft Foundry through Azure Speech and with direct API access through Microsoft Foundry:
– MAI-Transcribe-2-Streaming is available at an introductory price of $0.54 per hour of audio through the end of the year.
– MAI-Voice-2.1 is available at $22 per 1M characters
– MAI-Voice-2.1 Flash is available at $15 per 1M characters
We’re also excited to make these models available through additional platforms, including OpenRouter, Vercel, and LiveKit, giving developers more ways to discover, access, and build with MAI models.
*Source: Models | ElevenLabs Documentation