New Approach to Timbre Visualization

Chong, Kyrin Sethel; Sourin, Alexei

doi:10.1109/cw58918.2023.00036

Cited by 3 publications

(3 citation statements)

References 16 publications

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“…Inspired by the correspondence between audio spectral features and visual colors, we analyzed in our past study [21] the timbre features using spectral centroid and rolloff, strength of the sound onset, and MFCCs, which we then assigned to visual colors for different instruments. The user study indicated that regardless of musical education, there is a certain tendency to associate a musical instrument with visual colors.…”

Section: Music Timbre Visualizationmentioning

confidence: 99%

“…As a result, the cross-entropy loss function is applied to train the timbre classification model. Additionally, the results derived in [21] are applied to assign visual colors to music instruments. Since the IRMAS dataset provided the classification of 11 instruments, we mapped the individual instruments to a specific color, denoted in RGB values (Table . 2).…”

Section: Music Timbre Classificationmentioning

confidence: 99%

“…Note that there are only 10 columns because the human voice is excluded. For the musical instruments that were not studied in [21] (Acoustic Guitar, Electric Guitar, and Organ), we applied the same approaches to analyze the spectral features and MFCCs to derive their visual colors. Since the image generation process is based on text prompts, the classified timbre is mapped to text description of colors, providing an external control of color palette of the visual signature.…”

Section: Music Timbre Classificationmentioning

confidence: 99%

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Visual Signatures for Music Mood and Timbre

Wang,

Sourin

2024

Preprint

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Existing research on music visualization has primarily focused on creating animated visual illustrations to accompany the music being played based on fundamental attributes such as sound frequency or music structure, whereas the higher-level features, including mood and timbre, are mostly overlooked. In this paper, we propose visual signatures to describe the higher-level attributes of music, where the content and the color palette of the visual signatures are controlled by the music mood and timbre, respectively. We expect that the users with different cultural and educational backgrounds will be able to easily interpret the meaning of sound with the proposed visual signatures. In our work, we used a contrastive learning neural network for mood classification and an audio Transformer for timbre classification. The performance of the music classification models is examined by their accuracy, while multiple generated images are displayed to showcase the feasibility of visual signatures.

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Section: Music Timbre Visualizationmentioning

confidence: 99%

Section: Music Timbre Classificationmentioning

confidence: 99%

Section: Music Timbre Classificationmentioning

confidence: 99%

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Visual Signatures for Music Mood and Timbre

Wang,

Sourin

2024

Preprint

Self Cite

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Visual signatures for music mood and timbre

Wang,

Sourin

2024

Vis Comput

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How Did 19th-Century Alphorns Sound? A Reconstruction Based on Written Accounts of Its Musical Timbre

Wey

2024

Arts

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This paper reconstructs the sound of 19th-century alphorns based on contemporary written descriptions, which allows for a better understanding of literature and compositions that quoted and imitated the alphorn throughout the 19th century. In the absence of sound recordings, historical documents and literary sources provide valuable insights into the timbre of these traditional Alpine instruments. The research examines descriptions from 19th-century texts, comparing them with modern understandings of musical timbre. By analyzing the language used to describe the alphorn’s sound, the study identifies recurring descriptors and contextualizes them within the broader acoustic environment, including the influence of natural sounds like waterfalls and echoes. Historical sources reveal a complex perception of the alphorn’s timbre, described in terms of its resemblance to muted trumpets and a blend of brass and woodwind qualities. Authors such as Hermann Alexander von Berlepsch and François-Joseph Fétis provided detailed accounts, noting contrasting characteristics like “rough”, “soft”, “sharp”, and “melodious”, which varied with the listener’s distance from the instrument. These descriptions highlight the alphorn’s unique sound profile, distinct from modern perceptions that emphasize a warmer, fuller timbre. The findings underscore the importance of considering ecological and psychoacoustic contexts in the study of historical musical instruments.

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New Approach to Timbre Visualization

Cited by 3 publications

References 16 publications

Visual Signatures for Music Mood and Timbre

Visual Signatures for Music Mood and Timbre

Visual signatures for music mood and timbre

How Did 19th-Century Alphorns Sound? A Reconstruction Based on Written Accounts of Its Musical Timbre

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