Audio Curation Concepts#
This guide covers the essential concepts for audio data curation in NVIDIA NeMo Curator. These concepts assume basic familiarity with speech processing and machine learning principles.
Core Concept Areas#
Audio curation in NVIDIA NeMo Curator focuses on these key areas:
Modality-level overview of ingest, validation, optional ASR, metrics, filtering, and export
Comprehensive overview of the automatic speech recognition pipeline and workflow
Core concepts for evaluating speech transcription quality and audio characteristics
Understanding the AudioBatch data structure and audio file management
Concepts for constructing manifests and ingesting audio datasets
Concepts for integrating audio processing with text curation workflows
Infrastructure Components#
The audio curation concepts build on NVIDIA NeMo Curator’s core infrastructure components, which are shared across all modalities. These components include:
Optimize memory usage when processing large audio datasets
Leverage NVIDIA GPUs for faster ASR inference and audio processing
Continue interrupted operations across large audio datasets