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The 2007 MIREX Audio Mood Classification Task: Lessons Learned
Important issues in setting up the AMC task are described, dataset construction and ground-truth labeling are analyzed, and human assessments on the audio dataset, as well as system performances from various angles are analyzed.
The Music Information Retrieval Evaluation eXchange: Some Observations and Insights
- J. S. Downie, A. Ehmann, Mert Bay, M. C. Jones
- Computer ScienceAdvances in Music Information Retrieval
- 25 March 2010
This chapter outlines some of the major highlights of the past four years of MIREX evaluations, including its organizing principles, the selection of evaluation metrics, and the evolution of evaluation tasks.
Lyric Text Mining in Music Mood Classification
Findings show patterns at odds with findings in previous studies: audio features do not always outperform lyrics features, and combining lyrics and audio features can improve performance in many mood categories, but not all of them.
End-to-end Learning for Music Audio Tagging at Scale
- Jordi Pons, Oriol Nieto, Matthew Prockup, Erik M. Schmidt, A. Ehmann, X. Serra
- Computer ScienceISMIR
- 7 November 2017
This work focuses on studying how waveform-based models outperform spectrogram-based ones in large-scale data scenarios when datasets of variable size are available for training, suggesting that music domain assumptions are relevant when not enough training data are available.
The 2005 Music Information retrieval Evaluation Exchange (MIREX 2005): Preliminary Overview
This paper is an extended abstract which provides a brief preliminary overview of the 2005 Music Information Retrieval Evaluation eXchange (MIREX 2005) and lists of targets items to be undertaken before MIREX 2006 to ensure the ongoing success of the MIreX framework.
Melody Transcription From Music Audio: Approaches and Evaluation
- Graham E. Poliner, D. Ellis, A. Ehmann, E. Gómez, Sebastian Streich, B. Ong
- Computer ScienceIEEE Transactions on Audio, Speech, and Language…
- 1 May 2007
The results of full-scale evaluations of melody transcription systems conducted in 2004 and 2005 are described, including an overview of the systems submitted, details of how the evaluations were conducted, and a discussion of the results.
Evaluation of Multiple-F0 Estimation and Tracking Systems
This paper presents the systematic evaluations of over a dozen competing methods and algorithms for extracting the fundamental frequencies of pitched sound sources in polyphonic music.
Human Similarity Judgments: Implications for the Design of Formal Evaluations
This paper presents findings of a series of analyses of human similarity judgments from the Symbolic Melodic Similarity, and Audio Music Similarity tasks from the Music Information Retrieval…
Second Fiddle is Important Too: Pitch Tracking Individual Voices in Polyphonic Music
A method for tracking the pitches (F0s) of individual instruments in polyphonic music that uses a pre-learned dictionary of spectral basis vectors for each note for a variety of musical instruments and formulates the tracking of pitches of individual voices in a probabilistic manner.
Audio Cover Song Identification: MIREX 2006-2007 Results and Analyses
Analysis of the 2006 and 2007 results of the Music Information Retrieval Evaluation eXchange (MIREX) Audio Cover Song Identification (ACS) tasks indicate significant improvements in this domain have been made over the course of 2006-2007.