Papers Beat Tracking
“Beat Tracking” 태그가 달린 논문 24편 · 필터 해제
MulTTiPop: A Multitrack Transcription Dataset for Pop Music
We present MulTTiPop, a dataset of pop music segments and their associated multitrack MIDI recordings for the evaluation of automatic music transcription models. MulTTiPop contains 572 segments of popular music totaling …
Music TranscriptionBeat TrackingPHALAR: Phasors for Learned Musical Audio Representations
Stem retrieval, the task of matching missing stems to a given audio submix, is a key challenge currently limited by models that discard temporal information. We introduce PHALAR, a contrastive framework achieving a relat…
Beat TrackingJoint Estimation of Piano Dynamics and Metrical Structure with a Multi-task Multi-Scale Network
Estimating piano dynamic from audio recordings is a fundamental challenge in computational music analysis. In this paper, we propose an efficient multi-task network that jointly predicts dynamic levels, change points, be…
Beat TrackingMotionBeat: Motion-Aligned Music Representation via Embodied Contrastive Learning and Bar-Equivariant Contact-Aware Encoding
Music is both an auditory and an embodied phenomenon, closely linked to human motion and naturally expressed through dance. However, most existing audio representations neglect this embodied dimension, limiting their abi…
Representation LearningContrastive LearningEmotion RecognitionBeat TrackingTowards Human-in-the-Loop Onset Detection: A Transfer Learning Approach for Maracatu
We explore transfer learning strategies for musical onset detection in the Afro-Brazilian Maracatu tradition, which features complex rhythmic patterns that challenge conventional models. We adapt two Temporal Convolution…
Information RetrievalTransfer LearningBeat TrackingCMI-Bench: A Comprehensive Benchmark for Evaluating Music Instruction Following
Recent advances in audio-text large language models (LLMs) have opened new possibilities for music understanding and generation. However, existing benchmarks are limited in scope, often relying on simplified tasks or mul…
Beat TrackingGenre classificationInformation RetrievalInstruction Following+5Exploring GPT's Ability as a Judge in Music Understanding
Recent progress in text-based Large Language Models (LLMs) and their extended ability to process multi-modal sensory data have led us to explore their applicability in addressing music information retrieval (MIR) challen…
Beat TrackingInformation RetrievalMusic Information RetrievalPrompt EngineeringZero-shot Musical Stem Retrieval with Joint-Embedding Predictive Architectures
In this paper, we tackle the task of musical stem retrieval. Given a musical mix, it consists in retrieving a stem that would fit with it, i.e., that would sound pleasant if played together. To do so, we introduce a new …
Beat TrackingContrastive LearningRetrievalA Contrastive Self-Supervised Learning scheme for beat tracking amenable to few-shot learning
In this paper, we propose a novel Self-Supervised-Learning scheme to train rhythm analysis systems and instantiate it for few-shot beat tracking. Taking inspiration from the Contrastive Predictive Coding paradigm, we pro…
Beat TrackingFew-Shot LearningRhythmSelf-Supervised LearningBeat this! Accurate beat tracking without DBN postprocessing
We propose a system for tracking beats and downbeats with two objectives: generality across a diverse music range, and high accuracy. We achieve generality by training on multiple datasets -- including solo instrument re…
Beat TrackingDownbeat TrackingLocal Periodicity-Based Beat Tracking for Expressive Classical Piano Music
To model the periodicity of beats, state-of-the-art beat tracking systems use "post-processing trackers" (PPTs) that rely on several empirically determined global assumptions for tempo transition, which work well for mus…
Beat TrackingMusicLDM: Enhancing Novelty in Text-to-Music Generation Using Beat-Synchronous Mixup Strategies
Diffusion models have shown promising results in cross-modal generation tasks, including text-to-image and text-to-audio generation. However, generating music, as a special type of audio, presents unique challenges due t…
Audio GenerationBeat TrackingData AugmentationMusic Generation+1Zero-note samba: Self-supervised beat tracking
Supervised machine learning for music information retrieval requires a large annotated training set, and is thus an expensive and time-consuming process. To circumvent this problem, we propose to train deep neural networ…
Beat TrackingInformation RetrievalMusic Information RetrievalSelf-Supervised LearningAn Analysis Method for Metric-Level Switching in Beat Tracking
For expressive music, the tempo may change over time, posing challenges to tracking the beats by an automatic model. The model may first tap to the correct tempo, but then may fail to adapt to a tempo change, or switch b…
Beat TrackingJukeDrummer: Conditional Beat-aware Audio-domain Drum Accompaniment Generation via Transformer VQ-VAE
This paper proposes a model that generates a drum track in the audio domain to play along to a user-provided drum-free recording. Specifically, using paired data of drumless tracks and the corresponding human-made drum t…
Beat TrackingDecoderSinging Beat Tracking With Self-supervised Front-end and Linear Transformers
Tracking beats of singing voices without the presence of musical accompaniment can find many applications in music production, automatic song arrangement, and social media interaction. Its main challenge is the lack of s…
Beat TrackingSelf-Supervised Beat Tracking in Musical Signals with Polyphonic Contrastive Learning
Annotating musical beats is a very long and tedious process. In order to combat this problem, we present a new self-supervised learning pretext task for beat tracking and downbeat estimation. This task makes use of Splee…
Audio Source SeparationBeat TrackingContrastive LearningSelf-Supervised LearningDon't look back: an online beat tracking method using RNN and enhanced particle filtering
Online beat tracking (OBT) has always been a challenging task. Due to the inaccessibility of future data and the need to make inference in real-time. We propose Do not Look back! (DLB), a novel approach optimized for eff…
Beat TrackingOnline Beat TrackingShift If You Can: Counting and Visualising Correction Operations for Beat Tracking Evaluation
In this late-breaking abstract we propose a modified approach for beat tracking evaluation which poses the problem in terms of the effort required to transform a sequence of beat detections such that they maximise the we…
Beat TrackingTemporally Guided Music-to-Body-Movement Generation
This paper presents a neural network model to generate virtual violinist's 3-D skeleton movements from music audio. Improved from the conventional recurrent neural network models for generating 2-D skeleton data in previ…
Beat TrackingDecoder