Gemini 3.5 Transcribe - Google's latest speech-to-text model - AiBoss

What is Gemini 3.5 Transcribe?

Gemini 3.5 Transcribe is Google's latest speech-to-text model, supporting both real-time streaming and pre-recorded audio processing modes. The former achieves sub-second latency through the Live API, while the latter supports speaker attribution and word-level timestamps. Gemini 3.5 Transcribe can automatically clean up filler words and self-correct, recognize more than 85 languages and switch languages in real time, and customize specialized vocabulary. Its word error rate is as low as 2.6%, and it supports calling other Gemini models to complete complex tasks such as image generation.

Key features of Gemini 3.5 Transcribe

Real-time flow transcriptionProvides continuous two-way speech-to-text service with sub-second latency via the Live API.
Pre-recorded audio transcriptionProvides accurate transcription of audio files with speaker attribution and word-level timestamps via the Interactions API.
Intelligent text cleanupAutomatically remove filler words such as "um" and "ah", correct self-correcting statements, and output formatted text.
Custom vocabulary adaptationThe transcription results are adjusted based on the technical terms and special spellings provided by the user to accurately identify alphanumeric combinations such as postal codes and order numbers.
Multilingual automatic detectionIt supports automatic recognition and transcription of more than 85 languages and can handle real-time language switching and multiple accents and dialects.
Distinguishing between multiple speakersAccurately attribute the speech of up to three speakers in the pre-recorded audio.
Cross-model function callDuring transcription, other Gemini models can be invoked to perform complex tasks such as image generation and document analysis.
Screen Context Blending: Improve transcription accuracy in specific scenarios by combining device screen content and conversation history.

Technical principles of Gemini 3.5 Transcribe

End-to-end audio understandingThe model generates text directly from the original audio waveform, avoiding the accumulation of errors introduced by intermediate representations, while retaining paralinguistic information such as intonation and pauses in the speech for semantic disambiguation.
Native multimodal fusionBased on the Gemini 3.5 unified architecture, audio and text are jointly encoded in a shared Transformer attention space, enabling the model to establish a direct mapping between acoustic features and semantic concepts.
Context-aware reasoningIt simultaneously processes voice signals, screenshot text, and dialogue history through a long context window, and dynamically weights relevant contexts using a cross-attention mechanism to improve the recognition accuracy of proper nouns, file names, and domain terms.
Incremental streaming decodingIt adopts an adaptive block segmentation and speculative decoding strategy to perform local semantic integration while the audio input continues to arrive, balancing the need for low latency and output stability, and supporting real-time response and interruption handling in two-way interaction.

How to use Gemini 3.5 Transcribe

Developer access: Call the model in Google AI Studio or Gemini Enterprise Agent Platform via the Gemini API.
Real-time voice interactionCall using the Live API gemini-3.5-transcribe-live Achieve bidirectional streaming transcription.
Audio file processingCall using the Interactions API gemini-3.5-transcribe Perform offline transcription with timestamps.
macOS desktop versionUse voice to input, edit text, and call other model functions directly in the Gemini macOS app.
Android Input MethodEnable the Rambler feature in Gboard to automatically clean up voice input and support voice editing.
Chrome browserSoon, voice input and typing will be supported in any webpage input box.
Enterprise deploymentIntegrate into customer service and internal workflows through the Gemini Enterprise Agent Platform.
Third-party frameworkQuickly build voice applications using platforms that have integrated the Live API, such as Agora, LiveKit, and Vercel.

The core advantages of Gemini 3.5 Transcribe

Leading transcription accuracyThe error rate is as low as 4.0% for streaming scenarios and as low as 2.6% for non-streaming scenarios, and it can still accurately capture alphanumeric entities in noisy environments.
Significantly optimized latencyCompared to its predecessor Chirp 3, the final transcription delivery time is reduced by 70%, and the real-time streaming response reaches sub-second levels.
Intelligent semantic cleanupAutomatically removes filler words, corrects self-correcting statements, and outputs formatted text that can be used directly.
Seamless multilingual switchingIt automatically recognizes and transcribes more than 85 languages, and supports real-time language switching and multi-dialect accent adaptation during conversations.
Speaker precise attributionThe pre-recorded audio supports the differentiation of speeches from up to three speakers and includes word-level timestamps for easy backtracking and location.
Screen context awarenessBy combining device screen content with conversation history, the accuracy of file name, technical terms, and active document recognition is significantly improved.
Cross-model task collaborationBuilt-in Function Calling capability allows you to call other Gemini models during transcription to perform complex operations such as image generation and file analysis.

Gemini 3.5 Transcribe project address

Project official website：https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-5-transcribe/

Gemini 3.5 Transcribe vs. Competitors

Comparison Dimensions	Gemini 3.5 Transcribe	OpenAI GPT-4o-transcribe
position	Intelligent speech transcription model, supporting real-time streaming and pre-recorded audio.	GPT-4o architecture-specific transcription model, API hosting service
Word Error Rate WER	Flow cytometry 4.0% / Non-flow cytometry 2.6%	Approximately 2.5% (Clean audio, industry leader)
Real-time streaming delay	Sub-second, native bidirectional continuous streaming	Supports streaming, implemented via the Realtime API.
Intelligent text cleanup	Automatic removal of filler words, self-correction, and formatted output.	Not supported; output raw, conversational text.
Speaker attribution	Native support for differentiation of up to 3 people + word-level timestamps	Native support is not supported; the diarize endpoint must be called separately.

Application scenarios of Gemini 3.5 Transcribe

Real-time meeting intelligent minutesReal-time streaming transcription in multi-person meetings, automatically distinguishing speakers, cleaning up filler words, and using the Gemini model to instantly generate meeting summaries and to-do lists.
Multilingual customer service voice assistant: Build a voice customer service system with sub-second latency through Live API, automatically recognize customer language and switch in real time, and accurately identify key information such as order number and product model by combining custom vocabulary.
Medical and Legal Oral RecordsDoctors or lawyers can dictate medical records and court transcripts, and the model automatically cleans up and corrects its own statements and formats professional terminology, outputting standard documents that can be directly archived.
Cross-language real-time captioning and translationProvides multilingual real-time subtitles for live streaming and video conferencing, with automatic detection capability for 85+ languages, combined with real-time language switching to achieve seamless cross-language communication.
Voice-driven programming and office automationIn Google AI Studio or Gemini macOS applications, developers can generate code by describing their requirements with their voice, while office workers can use voice commands to invoke screen context to complete cross-application file summaries and image generation.