Barwise Music Structure Analysis with the Correlation Block-Matching Segmentation Algorithm
Music Structure Analysis (MSA) is a Music Information Retrieval task consisting of representing a song in a simplified, organized manner by breaking it down into sections typically corresponding to `chorus'', verse'', `solo'', etc. In this work, we extend an MSA algorithm called the Correlation Block-Matching (CBM) algorithm introduced by (Marmoret et al., 2020, 2022b). The CBM algorithm is a dynamic programming algorithm that segments self-similarity matrices, which are a standard description used in MSA and in numerous other applications. In this work, self-similarity matrices are computed from the feature representation of an audio signal and time is sampled at the bar-scale. This study examines three different standard similarity functions for the computation of self-similarity matrices. Results show that, in optimal conditions, the proposed algorithm achieves a level of performance which is competitive with supervised state-of-the-art methods while only requiring knowledge of bar positions. In addition, the algorithm is made open-source and is highly customizable.
Code (0)
등록된 구현이 없습니다.
Tasks
Information RetrievalMusic Information RetrievalRetrievalSimilar Papers 제목 키워드 기반
Barwise Compression Schemes for Audio-Based Music Structure Analysis
Music Structure Analysis (MSA) consists in segmenting a music piece in several distinct sections. We approach MSA within a compression framework, under the hypothesis that the structure is more easily revealed by a simpl…
Unsupervised Evaluation of Deep Audio Embeddings for Music Structure Analysis
Music Structure Analysis (MSA) aims to uncover the high-level organization of musical pieces. State-of-the-art methods are often based on supervised deep learning, but these methods are bottlenecked by the need for heavi…
Barwise Section Boundary Detection in Symbolic Music Using Convolutional Neural Networks
Current methods for Music Structure Analysis (MSA) focus primarily on audio data. While symbolic music can be synthesized into audio and analyzed using existing MSA techniques, such an approach does not exploit symbolic …
Boundary DetectionDeep Cross-Modal Correlation Learning for Audio and Lyrics in Music Retrieval
Little research focuses on cross-modal correlation learning where temporal structures of different data modalities such as audio and lyrics are taken into account. Stemming from the characteristic of temporal structures …
RetrievalCombinatorial music generation model with song structure graph analysis
In this work, we propose a symbolic music generation model with the song structure graph analysis network. We construct a graph that uses information such as note sequence and instrument as node features, while the corre…
Graph Neural NetworkMusic Generation