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Found 8 papers, 5 papers with code
The Song Describer Dataset: a Corpus of Audio Captions for Music-and-Language Evaluation
We introduce the Song Describer dataset (SDD), a new crowdsourced corpus of high-quality audio-caption pairs, designed for the evaluation of music-and-language models.
LP-MusicCaps: LLM-Based Pseudo Music Captioning
In addition, we trained a transformer-based music captioning model with the dataset and evaluated it under zero-shot and transfer-learning settings.
Textless Speech-to-Music Retrieval Using Emotion Similarity
We introduce a framework that recommends music based on the emotions of speech.
Music Playlist Title Generation Using Artist Information
Automatically generating or captioning music playlist titles given a set of tracks is of significant interest in music streaming services as customized playlists are widely used in personalized music recommendation, and well-composed text titles attract users and help their music discovery.
Toward Universal Text-to-Music Retrieval
This paper introduces effective design choices for text-to-music retrieval systems.
Music Playlist Title Generation: A Machine-Translation Approach
We propose a machine-translation approach to automatically generate a playlist title from a set of music tracks.
TräumerAI: Dreaming Music with StyleGAN
The goal of this paper to generate a visually appealing video that responds to music with a neural network so that each frame of the video reflects the musical characteristics of the corresponding audio clip.
Ranked #1 on
Music Auto-Tagging
on TimeTravel
(using extra training data)
Musical Word Embedding: Bridging the Gap between Listening Contexts and Music
Word embedding pioneered by Mikolov et al. is a staple technique for word representations in natural language processing (NLP) research which has also found popularity in music information retrieval tasks.
