Process Data for Audio Curation

Process audio data you’ve loaded into AudioBatch objects using NeMo Curator’s comprehensive audio processing capabilities.

NeMo Curator provides a specialized suite of tools for processing speech and audio data as part of the AI training pipeline. These tools help you transcribe, analyze, filter, and integrate audio datasets to ensure high-quality input for ASR model training and multimodal applications.

How it Works

NeMo Curator’s audio processing capabilities are organized into four main categories:

1. ASR Inference: Transcribe audio using NeMo Framework’s pretrained ASR models
2. Quality Assessment: Calculate and filter based on transcription accuracy metrics
3. Audio Analysis: Extract audio characteristics like duration and validate formats
4. Text Integration: Convert processed audio data to text processing workflows

Each category provides GPU-accelerated implementations optimized for different speech curation needs. The result is a cleaned and filtered audio dataset with high-quality transcriptions ready for model training.

ASR Inference

Transcribe audio files using NeMo Framework’s state-of-the-art ASR models with GPU acceleration.

Quality Assessment

Evaluate and filter audio quality using transcription accuracy and audio characteristics.

Audio Analysis

Extract and analyze audio file characteristics for quality control and metadata generation.

Text Integration

Convert processed audio data to text processing workflows for multimodal applications.