Total matches
81
Detect emerging, bridge-candidate, and undercited papers inside a curated audio-ML corpus, then expose the signals behind every recommendation.
Search
Search v1 is intentionally narrow: lexical retrieval over titles and abstracts, plus practical filters for narrowing the current corpus. Semantic assist can come later, but it is not part of Search v1's scope.
Total matches
81
Visible window
61-75
Core papers shown
9
Rows with topics
9
Search v1 scope: dedicated lexical search, practical filters, and clean handoff into dossier and ranking views. When ranking family filtering is active, the API resolves and returns one explicit run context.
Query surface
title + abstract.Topic labels are imported metadata and can be noisy; use them as coarse navigation hints, not authoritative classifications.
Workflow map
01
Start with lexical retrieval and narrow with year, venue, topic, and scope filters until the candidate set is focused enough to inspect.
02
Open the paper dossier to review abstract, metadata, ranking presence, and adjacent papers without losing the corpus framing.
03
Use Recommended and Evaluation to understand why a result matters now and how it sits inside the exact resolved ranking run when family filtering is active.
Lexical results
Resolved filters: scope all_included
Understanding music styles is essential for music information retrieval, personalized recommendation, and AI-assisted content creation. However, existing work typically addresses tasks such as emotion classification and singing style class...
Abstract This research endeavor presents a rigorous interdisciplinary investigation into the emotional and narrative functions of " Let It Go " ( Frozen ) and " Show Yourself " ( Frozen II ), addressing a gap in scholarship that primarily...
This article details a correction to: Gómez-Marín, D., Ospina-Caicedo, R., Díaz-Cely, J., Paz, J., Jordà, S. and Herrera, P. (2024) 'Salsa, a Dataset for Beat Estimation in Salsa Music', Transactions of the International Society for Music...
Within music information retrieval (MIR) research, numerous beat‑tracking systems have been developed, targeting either audio recordings or symbolic representations such as MIDI files. However, the differences between these approaches, the...
The Real World Computing (RWC) Music Database has been a widely used and valuable resource in music information retrieval (MIR) research for over two decades, offering high‑quality audio recordings and comprehensive annotations for a varie...
Identifying instruments in polyphonic audio is challenging due to overlapping spectra and variations in timbre and playing styles. This task is central to music information retrieval, with applications in transcription, recommendation, and...
Music Question--Answering (MQA) is a machine learning task where a computational system analyzes and answers questions about music-related data. Traditional methods prioritize audio, overlooking visual and embodied aspects crucial to music...
This paper introduces ORD-CC32 , an open research dataset derived from the 1932 Cairo Congress of Arab Music recordings, a historically significant collection representing diverse Arab musical traditions. The dataset includes structured me...
Selective Annotation of Few Data for Beat Tracking of Latin American Music Using Rhythmic Features
lex 0.286Training state-of-the-art beat tracking models usually requires large amounts of annotated data. It is widely known that data annotation is a time-consuming process and generally involves expert knowledge in the context of MIR. This can be...
Re(de)fining Sonification: Project Classification Strategies in the Data Sonification Archive
lex 0.286This study focuses on a corpus of 445 sonification projects currently available in the Data Sonification Archive (DSA). The DSA develops in a collaborative process that involves researchers and creative communities, and has been online sin...
Recent advances in automatic piano transcription have enabled large scale analysis of piano music in the symbolic domain. However, the research has largely focused on classical piano music. We present PiJAMA (Piano Jazz with Automatic MIDI...
Wagner Ring Dataset: A Complex Opera Scenario for Music Processing and Computational Musicology
lex 0.286This paper introduces the Wagner Ring Dataset (WRD), a multi-modal and multi-version resource on the large-scale opera cycle Der Ring des Nibelungen by Richard Wagner. The Ring comprises four music dramas organized into eleven acts and 21...
Throughout history, a consistent temporal and spatial gap has persisted between the inception of novel knowledge and technology and their subsequent adoption for extensive practical utilization. The article explores the dynamic interaction...
Barwise Music Structure Analysis with the Correlation Block-Matching Segmentation Algorithm
lex 0.286Music 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 w...
Given a music recording, music structure analysis aims at identifying important structural elements and segmenting the recording according to these elements. In jazz music, a performance is often structured by repeating harmonic schemata (...