# CoverHunter: Cover Song Identification with Refined Attention and Alignments

arXiv: https://arxiv.org/abs/2306.09025 · HTML: https://mlsanity.com/paper/2306.09025/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 24 references that are in the map.
- First posted on arXiv 15 Jun 2023.

## Builds on (most cited first, 8 of 8)

- [FaceNet: A Unified Embedding for Face Recognition and Clustering](https://mlsanity.com/paper/1503.03832/) (2015)
- [Conformer: Convolution-augmented Transformer for Speech Recognition](https://mlsanity.com/paper/2005.08100/) (2020)
- [Bag of Tricks and A Strong Baseline for Deep Person Re-identification](https://mlsanity.com/paper/1903.07071/) (2019)
- [MUSAN: A Music, Speech, and Noise Corpus](https://mlsanity.com/paper/1510.08484/) (2015)
- [Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net](https://mlsanity.com/paper/1807.09441/) (2018)
- [Attentive Statistics Pooling for Deep Speaker Embedding](https://mlsanity.com/paper/1803.10963/) (2018)
- [ByteCover: Cover Song Identification via Multi-Loss Training](https://mlsanity.com/paper/2010.14022/) (2020)
- [Learning a Representation for Cover Song Identification Using Convolutional Neural Network](https://mlsanity.com/paper/1911.00334/) (2019)

## Built on by (most cited first, 6 of 6)

- [Exploring Musical Roots: Applying Audio Embeddings to Empower Influence Attribution for a Generative Music Model](https://mlsanity.com/paper/2401.14542/) (2024)
- [MAIA: An Inpainting-Based Approach for Music Adversarial Attacks](https://mlsanity.com/paper/2509.04980/) (2025)
- [Music Plagiarism Detection: Problem Formulation and a Segment-based Solution](https://mlsanity.com/paper/2601.21260/) (2026)
- [Real-world Music Plagiarism Detection With Music Segment Transcription System](https://mlsanity.com/paper/2509.08282/) (2025)
- [Scalable Music Cover Retrieval Using Lyrics-Aligned Audio Embeddings](https://mlsanity.com/paper/2601.11262/) (2026)
- [Rubato: Transcribing Piano Music with Timestamps](https://mlsanity.com/paper/2605.24291/) (2026)

## Abstract (arXiv)

Abstract: Cover song identification (CSI) focuses on finding the same music with different versions in reference anchors given a query track. In this paper, we propose a novel system named CoverHunter that overcomes the shortcomings of existing detection schemes by exploring richer features with refined attention and alignments. CoverHunter contains three key modules: 1) A convolution-augmented transformer (i.e., Conformer) structure that captures both local and global feature interactions in contrast to previous methods mainly relying on convolutional neural networks; 2) An attention-based time pooling module that further exploits the attention in the time dimension; 3) A novel coarse-to-fine training scheme that first trains a network to roughly align the song chunks and then refines the network by training on the aligned chunks. At the same time, we also summarize some important training tricks used in our system that help achieve better results. Experiments on several standard CSI datasets show that our method significantly improves over state-of-the-art methods with an embedding size of 128 (2.3% on SHS100K-TEST and 17.7% on DaTacos).