ASR

Audio transcription to text in a backend environment requires server-side processing, where you initialize the z-ai-web-dev-sdk, encode your audio files as base64 data, and call the asr.create API endpoint to receive accurate text output.

Yes, base64 audio data is required for speech-to-text processing with this approach, as the backend workflow specifically depends on sending base64-encoded audio payloads to the SDK's asr.create endpoint to generate accurate text transcripts.

The best way to transcribe meetings and podcasts into text is by using the z-ai-web-dev-sdk to process your audio files server-side, converting spoken content into searchable transcripts suitable for documentation and accessibility.

The z-ai-web-dev-sdk supports both batch and real-time speech-to-text transcription tasks for applications, handling common audio formats to convert spoken audio into accurate text via the asr.create API.

Speech-to-text transcription requires backend code because the z-ai-web-dev-sdk processes audio server-side, ensuring that base64 audio preparation and the asr.create API execution happen securely without exposing processing logic to the client.

Server-side audio transcription requires base64 encoding of audio data and backend implementation using the z-ai-web-dev-sdk, meaning you need server resources to handle the asr.create API calls for converting speech into text.