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

What is Gemini 3.5 Transcribe

Gemini 3.5 Transcribe is Google's latestspeech-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-corrections, recognize over 85 languages with real-time language switching, and customize specialized vocabulary, with a word error rate as low as 2.6%, and supports calling other Gemini models to complete complex tasks such as image generation.

Main features of Gemini 3.5 Transcribe

• Real-time streaming transcription: Provides continuous bidirectional speech-to-text service with sub-second latency through the Live API.
• Pre-recorded audio transcription: Provides accurate transcription of recorded files with speaker attribution and word-level timestamps through the Interactions API.
• Intelligent text cleanup: Automatically removes filler words such as "um" and "ah", corrects self-corrected statements, and outputs formatted text.
• Custom vocabulary adaptation: Adjusts transcription results based on user-provided specialized terminology and special spellings, and accurately recognizes alphanumeric combinations such as postal codes and order numbers.
• Automatic multilingual detection: Supports automatic recognition and transcription of over 85 languages, and can handle real-time language switching and multiple accents and dialects.
• Multi-speaker distinction: Accurately attributes the speech content of up to three speakers in pre-recorded audio.
• Cross-model function calling: During transcription, other Gemini models can be called to perform complex tasks such as image generation and file analysis.
• Screen context fusion: Combines device screen content and conversation history to improve transcription accuracy in specific scenarios.

Technical principles of Gemini 3.5 Transcribe

• End-to-end audio understanding: The model generates text directly from raw audio waveforms, avoiding error accumulation introduced by intermediate representations, while retaining paralinguistic information such as intonation and pauses in speech for semantic disambiguation.
• Native multimodal fusion: Based on the unified Gemini 3.5 architecture, audio and text are jointly encoded in a shared Transformer attention space, enabling the model to establish direct mappings between acoustic features and semantic concepts.
• Context-aware reasoning: Processes speech signals, screenshot text, and conversation history simultaneously through a long context window, and uses a cross-attention mechanism to dynamically weight relevant context, improving recognition accuracy for proper nouns, file names, and domain terminology.
• Incremental streaming decoding: Uses adaptive chunking and speculative decoding strategies to perform local semantic integration while audio input continues to arrive, balancing low-latency requirements with output stability, and supporting instant responses and interruption handling in bidirectional interaction.

How to use Gemini 3.5 Transcribe