Testing reliability of Mirtoolbox

Kumar, Neeraj; Kumar, Raubin; Bhattacharya, Sangeeta

doi:10.1109/ecs.2015.7125004

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…As mentioned earlier, the mirmode function in MIR toolbox (version 1.8.1, Lartillot et al, 2008) provides a similar estimation, but this is known to be unreliable (Kumar et al, 2015). Nonetheless, as MIR toolbox is widely used in the field of music cognition, we felt colleagues might benefit from knowing its performance in this type of task.…”

Section: Composermentioning

confidence: 90%

“…Tools such as MIR toolbox offer the ability to automatically estimate where stimuli fall on the major/minor spectrum. However, there are no systematic evaluations of this algorithm, and some studies utilising the feature have noted issues with MIR toolbox's consistency and reliability (Kumar, Kumar, & Bhattacharya, 2015). We will later examine the accuracy of this implementation.…”

Section: Key-finding Approachesmentioning

confidence: 99%

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Major-minorness in Tonal music -- Evaluation of Relative Mode Estimation using Expert Ratings and Audio-Based Key-finding Principles

Eerola,

Schutz

2023

Preprint

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Mode is a fundamental concept in Western music theory, as well as many aspects of music perception. It is foundational to tasks ranging from identifying chords, detecting cadences, and assessing form, as well as the encoding/decoding of musical emotion and expression. Here we expand the categorical notion of mode as major or minor to a continuum, an approach we refer to as relative mode. We formulate and evaluate a computational model that calculates this property from either symbolic or audio representations of music. Building on common key-finding techniques created to identify mode in a categorical manner, here we use them to infer the relative mode based on the difference between the potential key candidate strengths in major and minor keys. The model evaluation is based on a corpus consisting of excerpts from Preludes by Bach, Chopin, and Shostakovich previously assessed by expert music analysts. Our results suggest that the model is able to predict the relative mode to a degree that closely matches evaluations by experts using both audio and notated scores. A pragmatic set of parameters for the model is identified and the shortcomings and the applicability of the model to other eras and genres are discussed

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Section: Composermentioning

confidence: 90%

Section: Key-finding Approachesmentioning

confidence: 99%

Major-minorness in Tonal music -- Evaluation of Relative Mode Estimation using Expert Ratings and Audio-Based Key-finding Principles

Eerola,

Schutz

2023

Preprint

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Challenges and Opportunities of Predicting Musical Emotions with Perceptual and Automatized Features

Lange

Frieler

2018

Music Perception

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Music information retrieval (MIR) is a fast-growing research area. One of its aims is to extract musical characteristics from audio. In this study, we assumed the roles of researchers without further technical MIR experience and set out to test in an exploratory way its opportunities and challenges in the specific context of musical emotion perception. Twenty sound engineers rated 60 musical excerpts from a broad range of styles with respect to 22 spectral, musical, and cross-modal features (perceptual features) and perceived emotional expression. In addition, we extracted 86 features (acoustic features) of the excerpts with the MIRtoolbox (Lartillot & Toiviainen, 2007). First, we evaluated the perceptual and extracted acoustic features. Both perceptual and acoustic features posed statistical challenges (e.g., perceptual features were often bimodally distributed, and acoustic features highly correlated). Second, we tested the suitability of the acoustic features for modeling perceived emotional content. Four nearly disjunctive feature sets provided similar results, implying a certain arbitrariness of feature selection. We compared the predictive power of perceptual and acoustic features using linear mixed effects models, but the results were inconclusive. We discuss critical points and make suggestions to further evaluate MIR tools for modeling music perception and processing.

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Testing reliability of Mirtoolbox

Cited by 2 publications

References 7 publications

Major-minorness in Tonal music -- Evaluation of Relative Mode Estimation using Expert Ratings and Audio-Based Key-finding Principles

Major-minorness in Tonal music -- Evaluation of Relative Mode Estimation using Expert Ratings and Audio-Based Key-finding Principles

Challenges and Opportunities of Predicting Musical Emotions with Perceptual and Automatized Features

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