ASR

Base64 encoding is required for audio transcription when handling API-driven backend workflows, allowing you to pass audio data directly within server-side payloads instead of using file paths.

Yes, you can use speech-to-text for meeting notes, podcast recordings, interviews, and voice memos by processing the audio files server-side to extract accurate spoken content as searchable text.

Yes, you need the z-ai-web-dev-sdk dependency to convert voice recordings into text, as it provides the core speech recognition capabilities required for executing the transcription scripts.

The best way to handle base64 audio input for speech-to-text conversion is to encode the source file before passing it to the server-side script, ensuring seamless API-driven transcription without direct file uploads.

Yes, this speech-to-text approach supports common formats like WAV and MP3, enabling you to directly transcribe standard audio files from voice memos or call recordings into plain text.