ASR

To transcribe base64 audio data to text in a Node.js backend, use the z-ai-web-dev-sdk to process base64-encoded inputs directly without requiring file IO. This enables backend transcription services for voice interfaces and content analysis.

Yes, you can use the z-ai-web-dev-sdk for streaming speech-to-text transcription. It supports production-ready workflows including streaming transcription via the z-ai CLI using the --stream flag for real-time audio processing.

The best way to convert speech to text without writing files to disk is passing base64-encoded audio data directly to a backend SDK. The z-ai-web-dev-sdk processes base64 inputs natively, bypassing file IO for immediate transcription.

Backend speech-to-text processing using this approach requires a Node.js runtime environment. It relies specifically on the z-ai-web-dev-sdk to execute transcription tasks and handle audio data within your backend services.

You can batch transcribe multiple audio files using the z-ai CLI by leveraging its production-ready workflows. The CLI supports processing audio files and outputting metadata-rich results to JSON for documentation and analytics.

A limitation of using base64 encoding for audio transcription is increased memory consumption, as encoding binary audio data into text expands payload size. This approach bypasses file IO but requires sufficient backend memory to process large base64 strings.