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Found 11 papers, 4 papers with code
miditok: A Python package for MIDI file tokenization
Recent progress in natural language processing has been adapted to the symbolic music modality.
Impact of time and note duration tokenizations on deep learning symbolic music modeling
Symbolic music is widely used in various deep learning tasks, including generation, transcription, synthesis, and Music Information Retrieval (MIR).
Byte Pair Encoding for Symbolic Music
When used with deep learning, the symbolic music modality is often coupled with language model architectures.
An adaptive music generation architecture for games based on the deep learning Transformer mode
To adapt the music generated to the game play and to the player(s) situation, we are using an arousal-valence model of emotions, in order to control the selection of musical layers.
From Procedures, Objects, Actors, Components, Services, to Agents -- A Comparative Analysis of the History and Evolution of Programming Abstractions
The objective of this chapter is to propose some retrospective analysis of the evolution of programming abstractions, from {\em procedures}, {\em objects}, {\em actors}, {\em components}, {\em services}, up to {\em agents}, %have some compare concepts of software component and of agent (and multi-agent system), %The method chosen is to by replacing them within a general historical perspective.
Music Tempo Estimation via Neural Networks -- A Comparative Analysis
This paper presents a comparative analysis on two artificial neural networks (with different architectures) for the task of tempo estimation.
Energy Consumption of Deep Generative Audio Models
In most scientific domains, the deep learning community has largely focused on the quality of deep generative models, resulting in highly accurate and successful solutions.
From Artificial Neural Networks to Deep Learning for Music Generation -- History, Concepts and Trends
The current wave of deep learning (the hyper-vitamined return of artificial neural networks) applies not only to traditional statistical machine learning tasks: prediction and classification (e. g., for weather prediction and pattern recognition), but has already conquered other areas, such as translation.
Music Generation by Deep Learning - Challenges and Directions
In addition to traditional tasks such as prediction, classification and translation, deep learning is receiving growing attention as an approach for music generation, as witnessed by recent research groups such as Magenta at Google and CTRL (Creator Technology Research Lab) at Spotify.
Deep Learning Techniques for Music Generation -- A Survey
Examples are: scalar, one-hot or many-hot.
A Hybrid Architecture for Multi-Party Conversational Systems
Multi-party Conversational Systems are systems with natural language interaction between one or more people or systems.
