Definition
The critical preprocessing stage in multi-modal RAG pipelines where unstructured audio data is converted into normalized text, enabling speech-based assets to be indexed, embedded, and queried by an LLM. It often involves a trade-off between Word Error Rate (WER) and inference latency, particularly when dealing with real-time AI Agents.
In AI engineering, this is the ETL process for voice, not merely a consumer dictation tool.
"A court reporter translating a live hearing into a searchable legal transcript to be filed in a library's archive."
- Speaker Diarization(Component: The process of attributing transcribed text to specific individuals for multi-turn agent memory.)
- Vector Embedding(Downstream Process: The mathematical representation of the resulting transcript for semantic retrieval.)
- Word Error Rate (WER)(Metric: The standard for measuring the accuracy of the ingestion layer in a RAG pipeline.)
- Timestamp Alignment(Component: Mapping text to specific audio segments to allow agents to provide 'click-to-play' citations.)
Conceptual Overview
The critical preprocessing stage in multi-modal RAG pipelines where unstructured audio data is converted into normalized text, enabling speech-based assets to be indexed, embedded, and queried by an LLM. It often involves a trade-off between Word Error Rate (WER) and inference latency, particularly when dealing with real-time AI Agents.
Disambiguation
In AI engineering, this is the ETL process for voice, not merely a consumer dictation tool.
Visual Analog
A court reporter translating a live hearing into a searchable legal transcript to be filed in a library's archive.