max-audio-classifier
A deep learning model that classifies sounds in 10-second audio clips into 527 categories from the AudioSet ontology.
What is max-audio-classifier?
IBM MAX Audio Classifier is a deep learning model that identifies and classifies sounds within 10-second audio clips. It uses a multi-attention classifier trained on the Google AudioSet dataset to predict the top five sound categories from a vocabulary of 527 labels, such as music, speech, rain, or thunder. The model solves the problem of automated audio event detection, converting raw audio into structured semantic labels.
Developers and researchers building applications that require automated sound recognition, such as content moderation systems, multimedia indexing tools, smart home devices, or audio analysis pipelines.
Developers choose this model because it provides a production-ready, pre-trained audio classifier that can be easily deployed via Docker, eliminating the need to collect massive datasets or train complex models from scratch. Its integration into the IBM MAX ecosystem ensures reliable performance and straightforward API access.
Overview
Identify sounds in short audio clips
Use Cases
Best For
- Automatically tagging sounds in user-uploaded audio or video content
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