Tell me about transcribing audio files into transcripts

Apple's WWDC session titled "Bring advanced speech-to-text to your app with SpeechAnalyzer" provides a comprehensive overview of how to transcribe audio files into transcripts using the SpeechAnalyzer API. The session covers the following key points:

1. SpeechAnalyzer API: The API allows developers to manage an analysis session and add a transcriber module to perform speech-to-text processing. This is done asynchronously, enabling the application to handle audio input and transcription results independently.

2. Volatile and Finalized Results: The transcriber can deliver both volatile (real-time, less accurate) and finalized (more accurate) results. Volatile results provide immediate feedback, which can be useful for live transcription experiences.

3. Transcription Process: The process involves setting up the SpeechAnalyzer with a transcriber module, configuring it with the desired locale, and handling the results. The transcription results are represented as attributed strings, which include timing data for synchronization with audio playback.

4. On-Device Processing: Transcription is performed entirely on-device, ensuring privacy. However, the necessary language models need to be downloaded and managed using the Asset Inventory API.

5. Integration with SwiftUI: The session demonstrates how to integrate the transcription results into a SwiftUI application, using attributed strings to visualize the transition from volatile to finalized results.

For more detailed information, you can refer to the session Bring advanced speech-to-text to your app with SpeechAnalyzer (09:06).