Methods for Combining Time-Frequency Representations: A Python Package

Boechat BA, da Costa MVM, Biscainho LWP. Methods for Combining Time-Frequency Representations: A Python Package. J Audio Eng Soc. 2026;74(5):336-348. doi:10.17743/jaes.2022.0266

@article{Boechat2026_23140,
  author = {Boechat, Bernardo A. and da Costa, Maurício V. M. and Biscainho, Luiz W. P.},
  title = {{Methods for Combining Time-Frequency Representations: A Python Package}},
  journal = {Journal of the Audio Engineering Society},
  volume = {74},
  number = {5},
  pages = {336--348},
  year = {2026},
  month = may,
  publisher = {Audio Engineering Society},
  doi = {10.17743/jaes.2022.0266},
  url = {https://doi.org/10.17743/jaes.2022.0266}
}

TY  - JOUR
TI  - Methods for Combining Time-Frequency Representations: A Python Package
AU  - Boechat, Bernardo A.
AU  - da Costa, Maurício V. M.
AU  - Biscainho, Luiz W. P.
T2  - Journal of the Audio Engineering Society
J2  - J. Audio Eng. Soc.
VL  - 74
IS  - 5
SP  - 336
EP  - 348
PY  - 2026
DA  - 2026/05/12
DO  - 10.17743/jaes.2022.0266
UR  - https://doi.org/10.17743/jaes.2022.0266
PB  - Audio Engineering Society
LA  - en
AB  - 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.
ER  -