Overview | NeMo Curator

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.

Concepts

Learn about AudioTask, ASR pipelines, and other core data structures for efficient audio curation data-structures asr-pipeline quality-metrics

Get Started

Learn prerequisites, setup instructions, and initial configuration for audio curation setup configuration quickstart

Curation Tasks

Load Data

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

Local Files

Load audio files from local directories and file systems local-storage file-discovery batch-processing

Custom Manifests

Create and load custom audio dataset manifests with metadata manifests metadata custom-formats

FLEURS Dataset

Load and process the multilingual FLEURS speech dataset fleurs multilingual benchmarks

Process Data

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

ASR Inference

Generate transcriptions using NVIDIA NeMo ASR models nemo-models transcription gpu-accelerated

Quality Assessment

Assess transcription quality using WER and CER wer-filtering duration-filtering

Audio Analysis

Analyze audio characteristics including duration and format validation duration-calculation format-validation metadata-extraction

Text Integration

Integrate audio processing results with text curation workflows multimodal text-filtering pipeline-integration

Save & Export

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

Save & Export

Export curated audio datasets with transcriptions and quality metrics manifests parquet metadata

Tutorials

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

Beginner Tutorial

Learn the basics of audio loading, ASR inference, and quality filtering asr-inference quality-filtering basic-workflow

Long-Form Audio Cutting

Turn long-form diarized recordings into mono, resampled snippet archives and manifests for audio language model pretraining alm-pretraining long-form-audio webdataset