# CLAP Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/clap
> Markdown URL: https://aitinkerers.org/technologies/clap.md
> Technology record last updated: 2026-04-20T23:19:05Z
> Generated: 2026-10-24T16:58:43Z

CLAP (Contrastive Language-Audio Pre-training) is a dual-encoder AI model that aligns audio and text embeddings for zero-shot classification and retrieval.

CLAP (Contrastive Language-Audio Pre-training) is a dual-encoder framework: it projects audio and text into a shared, multimodal space using contrastive learning. Accepted at ICASSP 2023, the model has been rigorously evaluated on 26 audio downstream tasks, achieving State-of-the-Art (SoTA) performance in several, including classification and retrieval. It is pretrained on large-scale data, such as LAION-Audio-630K, and utilizes advanced architectures (e.g., HTSAT-fused). This core capability enables 'Zero-Shot' inference, which removes the requirement for task-specific labeled audio data and provides flexible, open-vocabulary class prediction at inference time.

- Official technology site: https://github.com/microsoft/CLAP
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Multimodalidad en espacios vectoriales](https://bogota.aitinkerers.org/talks/rsvp_dSbIR9jaxqw)

- Event context: AI Tinkerers Bogotá - Febrero :) — 2025-02-27 — Bogotá
- Public talk page: https://bogota.aitinkerers.org/talks/rsvp_dSbIR9jaxqw

## Related Technologies

- [CLIP](https://aitinkerers.org/technologies/clip) ([Markdown](https://aitinkerers.org/technologies/clip.md)) — 10 public demos