***

description: >-
Comprehensive audio curation capabilities for speech data processing including
ASR inference, quality assessment, and text integration workflows
categories:

* workflows
  tags:
* audio-curation
* asr-inference
* speech-processing
* quality-metrics
* manifests
* text-integration
  personas:
* data-scientist-focused
* mle-focused
  difficulty: beginner
  content\_type: workflow
  modality: audio-only

***

# About Audio Curation

NeMo Curator provides comprehensive audio curation capabilities to prepare high-quality speech data for automatic speech recognition (ASR) and multi-modal model training. The toolkit includes processors for loading audio datasets, performing ASR inference, assessing transcription quality, and integrating with text curation workflows.

## Use Cases

* Process and curate large-scale speech datasets for ASR model training
* Perform quality assessment and filtering based on transcription accuracy metrics
* Generate transcriptions using state-of-the-art NVIDIA NeMo ASR models
* Integrate audio processing with text curation pipelines for multi-modal workflows
* Scale audio processing across GPU clusters efficiently

***

## Introduction

Master the fundamentals of NeMo Curator and set up your audio processing environment.

<Cards>
  <Card title="Concepts" href="/about/concepts/audio">
    Learn about AudioBatch, ASR pipelines, and other core data structures for efficient audio curation
    data-structures
    asr-pipeline
    quality-metrics
  </Card>

  <Card title="Get Started" href="/get-started/audio">
    Learn prerequisites, setup instructions, and initial configuration for audio curation
    setup
    configuration
    quickstart
  </Card>
</Cards>

## Curation Tasks

### Load Data

Import your audio data from various sources into NeMo Curator's processing pipeline.

<Cards>
  <Card title="Local Files" href="/curate-audio/load-data/local-files">
    Load audio files from local directories and file systems
    local-storage
    file-discovery
    batch-processing
  </Card>

  <Card title="Custom Manifests" href="/curate-audio/load-data/custom-manifests">
    Create and load custom audio dataset manifests with metadata
    manifests
    metadata
    custom-formats
  </Card>

  <Card title="FLEURS Dataset" href="/curate-audio/load-data/fleurs-dataset">
    Load and process the multilingual FLEURS speech dataset
    fleurs
    multilingual
    benchmarks
  </Card>
</Cards>

### Process Data

Transform and enhance your audio data through ASR inference, quality assessment, and analysis.

<Cards>
  <Card title="ASR Inference" href="/curate-audio/process-data/asr-inference">
    Generate transcriptions using NVIDIA NeMo ASR models
    nemo-models
    transcription
    gpu-accelerated
  </Card>

  <Card title="Quality Assessment" href="/curate-audio/process-data/quality-assessment">
    Assess transcription quality using WER and CER
    wer-filtering
    duration-filtering
  </Card>

  <Card title="Audio Analysis" href="/curate-audio/process-data/audio-analysis">
    Analyze audio characteristics including duration and format validation
    duration-calculation
    format-validation
    metadata-extraction
  </Card>

  <Card title="Text Integration" href="/curate-audio/process-data/text-integration">
    Integrate audio processing results with text curation workflows
    multimodal
    text-filtering
    pipeline-integration
  </Card>
</Cards>

### Save & Export

Save processed audio data and transcriptions in formats suitable for downstream training and analysis.

<Cards>
  <Card title="Save & Export" href="/curate-audio/save-export">
    Export curated audio datasets with transcriptions and quality metrics
    manifests
    parquet
    metadata
  </Card>
</Cards>

***

## Tutorials

Build practical experience with step-by-step guides for common audio curation workflows.

<Cards>
  <Card title="Beginner Tutorial" href="/curate-audio/tutorials/beginner">
    Learn the basics of audio loading, ASR inference, and quality filtering
    asr-inference
    quality-filtering
    basic-workflow
  </Card>
</Cards>
