Audio Fingerprinting

Audio fingerprinting is a technique for uniquely identifying audio recordings, typically songs, using compact representations of their spectral content. Current research focuses on improving the robustness of these fingerprints against noise and distortion, often employing deep learning models for denoising and enhancing peak-based algorithms, as well as exploring more efficient fingerprint storage and retrieval methods like holographic reduced representations. These advancements are crucial for enhancing the accuracy and scalability of music identification services and other applications requiring robust audio matching in real-world, noisy environments.