Emotion-Driven Melody Harmonization via Melodic Variation and Functional Representation

• URL: http://arxiv.org/abs/2407.20176v2
• Date: Wed, 25 Sep 2024 05:23:17 GMT
• Title: Emotion-Driven Melody Harmonization via Melodic Variation and Functional Representation
• Authors: Jingyue Huang, Yi-Hsuan Yang,
• Abstract summary: Emotion-driven melody aims to generate diverse harmonies for a single melody to convey desired emotions. Previous research found it hard to alter the perceived emotional valence of lead sheets only by harmonizing the same melody with different chords. In this paper, we propose a novel functional representation for symbolic music.
• Score: 16.790582113573453
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: Emotion-driven melody harmonization aims to generate diverse harmonies for a single melody to convey desired emotions. Previous research found it hard to alter the perceived emotional valence of lead sheets only by harmonizing the same melody with different chords, which may be attributed to the constraints imposed by the melody itself and the limitation of existing music representation. In this paper, we propose a novel functional representation for symbolic music. This new method takes musical keys into account, recognizing their significant role in shaping music's emotional character through major-minor tonality. It also allows for melodic variation with respect to keys and addresses the problem of data scarcity for better emotion modeling. A Transformer is employed to harmonize key-adaptable melodies, allowing for keys determined in rule-based or model-based manner. Experimental results confirm the effectiveness of our new representation in generating key-aware harmonies, with objective and subjective evaluations affirming the potential of our approach to convey specific valence for versatile melody.

Related papers

• Emotion-driven Piano Music Generation via Two-stage Disentanglement and Functional Representation [19.139752434303688]
  Managing the emotional aspect remains a challenge in automatic music generation. This paper explores the disentanglement of emotions in piano performance generation through a two-stage framework.
  arXiv  Detail & Related papers  (2024-07-30T16:29:28Z)
• Emotion Manipulation Through Music -- A Deep Learning Interactive Visual Approach [0.0]
  We introduce a novel way to manipulate the emotional content of a song using AI tools. Our goal is to achieve the desired emotion while leaving the original melody as intact as possible. This research may contribute to on-demand custom music generation, the automated remixing of existing work, and music playlists tuned for emotional progression.
  arXiv  Detail & Related papers  (2024-06-12T20:12:29Z)
• MeLFusion: Synthesizing Music from Image and Language Cues using Diffusion Models [57.47799823804519]
  We are inspired by how musicians compose music not just from a movie script, but also through visualizations. We propose MeLFusion, a model that can effectively use cues from a textual description and the corresponding image to synthesize music. Our exhaustive experimental evaluation suggests that adding visual information to the music synthesis pipeline significantly improves the quality of generated music.
  arXiv  Detail & Related papers  (2024-06-07T06:38:59Z)
• Emotion-Conditioned Melody Harmonization with Hierarchical Variational Autoencoder [11.635877697635449]
  We propose a novel LSTM-based Hierarchical Variational Auto-Encoder (LHVAE) to investigate the influence of emotional conditions on melody harmonization. LHVAE incorporates latent variables and emotional conditions at different levels to model the global and local music properties. Objective experimental results show that our proposed model outperforms other LSTM-based models.
  arXiv  Detail & Related papers  (2023-06-06T14:28:57Z)
• MeloForm: Generating Melody with Musical Form based on Expert Systems and Neural Networks [146.59245563763065]
  MeloForm is a system that generates melody with musical form using expert systems and neural networks. It can support various kinds of forms, such as verse and chorus form, rondo form, variational form, sonata form, etc.
  arXiv  Detail & Related papers  (2022-08-30T15:44:15Z)
• Re-creation of Creations: A New Paradigm for Lyric-to-Melody Generation [158.54649047794794]
  Re-creation of Creations (ROC) is a new paradigm for lyric-to-melody generation. ROC achieves good lyric-melody feature alignment in lyric-to-melody generation.
  arXiv  Detail & Related papers  (2022-08-11T08:44:47Z)
• Chord-Conditioned Melody Choralization with Controllable Harmonicity and Polyphonicity [75.02344976811062]
  Melody choralization, i.e. generating a four-part chorale based on a user-given melody, has long been closely associated with J.S. Bach chorales. Previous neural network-based systems rarely focus on chorale generation conditioned on a chord progression. We propose DeepChoir, a melody choralization system, which can generate a four-part chorale for a given melody conditioned on a chord progression.
  arXiv  Detail & Related papers  (2022-02-17T02:59:36Z)
• A-Muze-Net: Music Generation by Composing the Harmony based on the Generated Melody [91.22679787578438]
  We present a method for the generation of Midi files of piano music. The method models the right and left hands using two networks, where the left hand is conditioned on the right hand. The Midi is represented in a way that is invariant to the musical scale, and the melody is represented, for the purpose of conditioning the harmony.
  arXiv  Detail & Related papers  (2021-11-25T09:45:53Z)
• Music Gesture for Visual Sound Separation [121.36275456396075]
  "Music Gesture" is a keypoint-based structured representation to explicitly model the body and finger movements of musicians when they perform music. We first adopt a context-aware graph network to integrate visual semantic context with body dynamics, and then apply an audio-visual fusion model to associate body movements with the corresponding audio signals.
  arXiv  Detail & Related papers  (2020-04-20T17:53:46Z)
• Exploring Inherent Properties of the Monophonic Melody of Songs [10.055143995729415]
  We propose a set of interpretable features on monophonic melody for computational purposes. These features are defined not only in mathematical form, but also with some considerations on composers 'intuition. These features are considered by people universally in many genres of songs, even for atonal composition practices.
  arXiv  Detail & Related papers  (2020-03-20T14:13:16Z)
• Structural characterization of musical harmonies [4.416484585765029]
  We use a hybrid method in which an evidence-gathering numerical method detects modulation and then, based on the detected tonalities, a non-ambiguous grammar can be used for analyzing the structure of each tonal component. Experiments with music from the XVII and XVIII centuries show that we can detect the precise point of modulation with an error of at most two chords in almost 97% of the cases.
  arXiv  Detail & Related papers  (2019-12-27T23:15:49Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.