Code Switching in Real-Time | Universal-Streaming Speech-to-Text

2026-02-19 · Source: AssemblyAI · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, short

Summary

Assembly AI has updated its universal speech-to-text model to support real-time code switching across six languages: Spanish, English, Italian, French, German, and Portuguese. This advancement allows the model to transcribe conversations where speakers fluidly switch between these languages within a single forward pass, eliminating latency and delays. The model addresses a common problem in current phone dictation systems, which typically require users to manually switch language settings and adhere to a single language for accurate transcription. This new capability is particularly beneficial for multilingual individuals who frequently mix languages in their daily conversations, enabling seamless transcription without interruption or translation errors. A demonstration highlights its ability to transcribe mixed Spanish and English speech in real time.

Key takeaway

For AI Engineers developing audio applications for multilingual users, Assembly AI's updated universal model offers a significant advantage. Its real-time, code-switching capability across six languages can dramatically improve user experience by eliminating the need for manual language selection and reducing transcription errors in mixed-language speech. You should explore integrating this model via its API to enhance the functionality and accuracy of your applications for diverse linguistic contexts.

Key insights

Assembly AI's universal model enables real-time, zero-latency code-switched speech-to-text across six languages.

Principles

• Real-time transcription enhances multilingual communication.
• Single-pass processing eliminates latency in code-switching.

Method

The model processes speech containing multiple languages in a single forward pass, identifying and transcribing each language segment without requiring manual language selection or introducing delays.

In practice

• Integrate into multilingual audio applications via API.
• Use for dictation in mixed-language environments.

Topics

• Code Switching
• Real-time Speech-to-Text
• Multilingual AI
• Assembly AI
• Universal Model

Best for: AI Engineer, Software Engineer, Machine Learning Engineer

Related on AIssential

• English. Spanish. Race Car. No Problem. — AssemblyAI's Universal-3-Pro Streaming model excels at real-time transcription in extremely noisy, multilingual, and uncontrolled environments.
• TurnGuide: Enhancing Meaningful Full Duplex Spoken Interactions via Dynamic Turn-Level Text-Speech Interleaving — TurnGuide enhances full-duplex SLMs by planning turn-level text guidance before speech, improving semantic coherence and natural flow.
• Live demo of AssemblyAI's Universal-3.5 Pro Realtime Speech-to-Text model — Contextual prompting and noise suppression significantly enhance real-time speech-to-text accuracy across diverse languages and challenging audio environments.
• Deepgram speech-to-text and voice models now available natively on Together AI — Real-time voice agents require integrated STT, LLM, and TTS on a single platform to minimize latency and operational complexity.
• Can Voice Agents Handle Bilingual Customers? Benchmarking Frontier ASR on Code-Switched Speech — Frontier ASR models handle code-switched speech with minimal performance degradation, but error patterns vary by language pair and model.
• Introducing Post-Stream Refinement: Higher-Accuracy Real-Time Transcription — Post-Stream Refinement enhances real-time speech recognition by combining instant partial results with a higher-accuracy, context-aware second pass.

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Editorial summary, takeaway, and curation by AIssential. Original article published by AssemblyAI.