# Dynamic HumTrans: Humming Transcription Using CNNs and Dynamic Programming

arXiv: https://arxiv.org/abs/2410.05455 · HTML: https://mlsanity.com/paper/2410.05455/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 11 references that are in the map.
- First posted on arXiv 7 Oct 2024.

## Builds on (most cited first, 4 of 4)

- [A Lightweight Instrument-Agnostic Model for Polyphonic Note Transcription and Multipitch Estimation](https://mlsanity.com/paper/2203.09893/) (2022)
- [Melody transcription via generative pre-training](https://mlsanity.com/paper/2212.01884/) (2022)
- [Pseudo-Label Transfer from Frame-Level to Note-Level in a Teacher-Student Framework for Singing Transcription from Polyphonic Music](https://mlsanity.com/paper/2203.13422/) (2022)
- [HumTrans: A Novel Open-Source Dataset for Humming Melody Transcription and Beyond](https://mlsanity.com/paper/2309.09623/) (2023)

## Abstract (arXiv)

We propose a novel approach for humming transcription that combines a CNN-based architecture with a dynamic programming-based post-processing algorithm, utilizing the recently introduced HumTrans dataset. We identify and address inherent problems with the offset and onset ground truth provided by the dataset, offering heuristics to improve these annotations, resulting in a dataset with precise annotations that will aid future research. Additionally, we compare the transcription accuracy of our method against several others, demonstrating state-of-the-art (SOTA) results. All our code and corrected dataset is available at https://github.com/shubham-gupta-30/humming_transcription