ASR

To convert speech to text, this Skill uses the z-ai-web-dev-sdk backend to transcribe base64-encoded audio inputs, supporting formats like WAV, MP3, and M4A. It provides scripts with CLI and SDK examples to process audio files and retrieve accurate text results.

Yes, you can transcribe podcast audio and meeting recordings in batch mode. The Skill supports batch transcription workflows for common formats like WAV and MP3, converting spoken audio into searchable text for meeting minutes and interview notes.

The z-ai-web-dev-sdk supports real-time speech-to-text transcription workflows, including streaming output where supported. This enables voice-enabled UI commands and live processing for applications like meetings and interviews.

Base64 encoding is required for audio processing to safely transmit binary audio data through the z-ai-web-dev-sdk backend. This skill handles base64-encoded audio inputs to ensure robust speech-to-text transcription across supported formats like M4A and MP3.

The best way to handle speech-to-text for voice-enabled features is using this Skill's z-ai-web-dev-sdk integration. It processes base64-encoded audio inputs and provides CLI and SDK scripts to quickly implement transcription for voice commands and UI interactions.

When transcribing M4A audio files, limitations depend on the z-ai-web-dev-sdk backend's format support and streaming capabilities. This Skill handles base64-encoded M4A inputs for batch and real-time workflows, but users should verify streaming output support for their specific use case.