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Methods for Combining Time-Frequency Representations: A Python Package
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DOI：10.17743/jaes.2022.0266.png)
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Abstract
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This paper presents the main ideas behind ctfr, an extensible, user-friendly Python package for efficiently combining time-frequency representations (TFRs) of audio signals into a single representation that captures the best aspects of each, achieving high resolutions in both time and frequency. The authors develop and evaluate algorithmic tweaks and approximation schemes for existing TFR combination methods, with significant performance improvements over baseline implementations. In addition, combined TFRs are employed in training a deep learning system for note transcription from audio performances, showing improved results over traditional TFRs, thus demonstrating the effectiveness of using combination methods in audio processing and music information retrieval pipelines.
Keywords:
audio signal processing
combined time-frequency representation
constant Q transform
music information retrieval
short-time Fourier transform
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