openSMILE

Open Source

The industry-standard toolkit for real-time audio feature extraction and affective computing.

Capabilities: Emotion Recognition Speaker Identification Speech Health Diagnostics Musical Information Retrieval Voice Activity Detection

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9.5

Protocol Reliability Score

Overview

openSMILE (open-source Speech and Music Interpretation by Large-space Extraction) is a modular, high-performance toolkit for extracting a massive range of audio features from speech and music signals. Developed by audEERING GmbH and based on foundational research from the Technical University of Munich, it has become the gold standard in the scientific community for emotion recognition and speech-based health monitoring. In the 2026 market landscape, openSMILE is critical for developers building 'EQ-enabled' AI agents, providing the low-level acoustic descriptors (LLDs) necessary for Large Language Models to interpret prosody, stress, and emotional nuance. Its architecture supports real-time, incremental processing with extreme efficiency, allowing for deployment on edge devices and high-throughput cloud environments. The toolkit includes standardized feature sets like eGeMAPS and ComParE, ensuring reproducibility across research and commercial applications. While the core engine is open-source under LGPL/GPL licenses, its commercial adoption is driven by its ability to bridge the gap between raw waveforms and sophisticated machine learning classifiers, making it an essential component of any multimodal AI stack.