Transcription Architecture: Batch vs. Live
Gemini 3.5 Transcribe offers two distinct operational modes, allowing developers to choose the right tool based on the audio source:
- Batch Processing: Designed for existing audio files stored in cloud environments (e.g., Google Cloud Storage). This is ideal for analyzing large archives of customer calls, meetings, or interviews.
- Live Transcription: Optimized for real-time streaming, enabling use cases like live captioning or hands-free dictation where low-latency text output is required.
Both modes provide built-in features such as automatic language detection, speaker diarization (identifying individual speakers), and word-level timestamps, reducing the need to stitch together multiple disparate services.
Enhancing Accuracy with Custom Vocabulary
Generic speech-to-text models often struggle with domain-specific terminology, such as medical, legal, or financial jargon. Gemini 3.5 Transcribe addresses this through custom vocabulary biasing. By providing a list of industry-specific terms (e.g., "Nissen fundoplication" or "pyrosis"), developers can significantly improve transcription accuracy in specialized environments. This feature is particularly effective for high-stakes scenarios where precision is required for documentation or compliance.
From Transcription to Actionable Intelligence
Transcription is treated as the foundational step in a larger data pipeline. Once raw audio is converted into structured text, it can be passed to other Gemini models (such as Gemini 1.5 Flash) to perform higher-level reasoning. Common post-transcription workflows include:
- Sentiment Analysis: Automatically scoring customer frustration levels during support calls.
- Summarization: Extracting key takeaways and resolution status from long-form audio.
- Dashboarding: Aggregating insights across thousands of calls to track customer experience trends at scale.
By chaining these models, developers can move from raw audio input to structured, intelligent data outputs without needing to train custom models or manage complex infrastructure.