
Explore chaotic systems for audio generation and transformation. Learn about fixed points, bifurcation, and practical applications with interactive visualizations and code examples.

Explore requirements, challenges, and solutions for building a music assessment engine, including technical limitations and performance demonstrations on real-life data.

Explore digital audio signal processing, from continuous acoustic to discrete digital signals. Learn sampling theory, filtering, and time-frequency domain transformations through practical methods and hands-on exercises.

Explore real-time AI audio processing with Neutone plugin. Learn to integrate deep learning models into DAWs, experiment with timbre transfer, and develop innovative audio effects.

Explore audio-to-MIDI plugin development, transforming audio input into MIDI events for creative music production workflows. Learn techniques for real-time content analysis and feature extraction.

Explore approaches to pitch-shifting music and time-stretching, from simple overlap-add to FFT-based effects and frequency-domain techniques. Gain insights into designing a polyphonic pitch/time C++ library.

Explore an automatic circuit solving library for simulating analog audio circuits. Learn to implement and analyze component-level circuits for real-time plugins and mobile apps.

Optimize real-time audio processing libraries with practical strategies, measurement techniques, and performance-enhancing tricks. Gain tools for confident code optimization across platforms.

Explore a new graphical programming language bridging AI research and audio software development. Learn about its functional programming concepts, data handling capabilities, and flexible algorithm implementation.

Explore accelerated audio computing advancements: technology progress, use cases, SDK vision, and industry standards. Engage in shaping the future of GPU-powered audio processing.

Streamline car audio post-processing development with AudioworX. Learn about its framework, tuning tools, measurement module, and simulation environment for efficient audio software creation.

Explore pruning and quantization techniques to enhance efficiency of complex audio models for real-time processing in resource-constrained environments. Gain insights into model compression for audio applications.

Explore lock-in detection techniques for signal processing and measurement applications. Learn principles, implementation, and practical uses in various scientific fields.

Explore innovative approaches to audio deep learning, addressing practical challenges in efficiency, unsupervised learning, and resource-limited scenarios for enhanced audio processing and source separation.

Explore deep neural networks for sound classification, covering speech, music, and environmental sounds. Learn about AudioSet ontology and applications in bioacoustics and cross-modal learning.

Explore computational sound scene analysis, covering tasks from basic classification to advanced localization and captioning, with deep learning techniques and data requirements.

Explore multiclass audio segmentation techniques for broadcast environments, focusing on cutting-edge approaches and practical applications.

Explore acoustic scene analysis, complex modulations, and innovative filtering techniques for separating overlapping sound sources in noisy environments.

Explore techniques for music retrieval using Query by Humming, including string-alignment algorithms and hidden Markov models. Compare approaches and their effectiveness in finding songs from sung queries.

Explore audio source separation techniques, from basis functions to exemplars, and learn how to achieve direct computation of tasks like noisy speech recognition without intermediate separation steps.

Explore voice authentication privacy challenges and solutions, including cryptographic methods and secure binary embeddings for protecting user voice prints while enabling authentication.