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mjhydri/BeatNet ★ 522 83 APPLICATION

BeatNet is a Python library for real-time and offline music beat, downbeat, tempo, and meter tracking. It provides a complete system comprising a CRNN-based neural network for feature extraction, particle filtering for causal inference, and DBN for non-causal inference. The library supports four operational modes: streaming (microphone input), real-time (file processing), online (fast file processing), and offline (DBN-based). Beyond inference, it includes a complete training pipeline for training the CRNN model on custom datasets with data preparation tools, dataset handling, and validation procedures. The architecture is modular with clear separation between feature extraction, neural network modeling, and inference algorithms.

RATING: 7.2/10 MAINT: maintained DRIFT: low
#beat-tracking #music-information-retrieval #real-time-audio-processing #particle-filtering #crnn #audio-feature-extraction #beatnet #real-time #real-time-beat-tracker #real-time-downbeat-tracker #real-time-tempo #dnn-beat-tracking #pytorch #meter-detection #crnn-network #joint-model #online-time-signature-detection #downbeat-tracking #state-of-the-art
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