Results 11 to 20 of about 3,247,927 (340)
Simple and Controllable Music Generation [PDF]
Neural Information Processing Systems, 2023 We tackle the task of conditional music generation. We introduce MusicGen, a single Language Model (LM) that operates over several streams of compressed discrete music representation, i.e., tokens.
Jade Copet +7 more
semanticscholar +1 more source
MusicLM: Generating Music From Text [PDF]
arXiv.org, 2023 We introduce MusicLM, a model generating high-fidelity music from text descriptions such as"a calming violin melody backed by a distorted guitar riff".
A. Agostinelli +12 more
semanticscholar +1 more source
AI Choreographer: Music Conditioned 3D Dance Generation with AIST++ [PDF]
IEEE International Conference on Computer Vision, 2021 We present AIST++, a new multi-modal dataset of 3D dance motion and music, along with FACT, a Full-Attention Cross-modal Transformer network for generating 3D dance motion conditioned on music.
Ruilong Li +3 more
semanticscholar +1 more source
LP-MusicCaps: LLM-Based Pseudo Music Captioning [PDF]
International Society for Music Information Retrieval Conference, 2023 Automatic music captioning, which generates natural language descriptions for given music tracks, holds significant potential for enhancing the understanding and organization of large volumes of musical data.
Seungheon Doh +3 more
semanticscholar +1 more source
MuLan: A Joint Embedding of Music Audio and Natural Language [PDF]
International Society for Music Information Retrieval Conference, 2022 Music tagging and content-based retrieval systems have traditionally been constructed using pre-defined ontologies covering a rigid set of music attributes or text queries. This paper presents MuLan: a first attempt at a new generation of acoustic models
Qingqing Huang +5 more
semanticscholar +1 more source
VampNet: Music Generation via Masked Acoustic Token Modeling [PDF]
International Society for Music Information Retrieval Conference, 2023 We introduce VampNet, a masked acoustic token modeling approach to music synthesis, compression, inpainting, and variation. We use a variable masking schedule during training which allows us to sample coherent music from the model by applying a variety ...
H. F. García +3 more
semanticscholar +1 more source
MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training [PDF]
Findings, 2021 Symbolic music understanding, which refers to the understanding of music from the symbolic data (e.g., MIDI format, but not audio), covers many music applications such as genre classification, emotion classification, and music pieces matching. While good
Mingliang Zeng +5 more
semanticscholar +1 more source
Video Background Music Generation with Controllable Music Transformer [PDF]
ACM Multimedia, 2021 In this work, we address the task of video background music generation. Some previous works achieve effective music generation but are unable to generate melodious music specifically for a given video, and none of them considers the video-music rhythmic ...
Shangzhe Di +7 more
semanticscholar +1 more source
MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment [PDF]
AAAI Conference on Artificial Intelligence, 2017 Generating music has a few notable differences from generating images and videos. First, music is an art of time, necessitating a temporal model. Second, music is usually composed of multiple instruments/tracks with their own temporal dynamics, but ...
Hao-Wen Dong +3 more
semanticscholar +1 more source
librosa: Audio and Music Signal Analysis in Python
SciPy, 2015 This document describes version 0.4.0 of librosa: a Python pack- age for audio and music signal processing. At a high level, librosa provides implementations of a variety of common functions used throughout the field of music information retrieval.
Brian McFee +6 more
semanticscholar +1 more source