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Found 11 papers, 5 papers with code
ByteComposer: a Human-like Melody Composition Method based on Language Model Agent
Large Language Models (LLM) have shown encouraging progress in multimodal understanding and generation tasks.
Joint Music and Language Attention Models for Zero-shot Music Tagging
However, previous music tagging research primarily focuses on close-set music tagging tasks which can not be generalized to new tags.
ByteCover3: Accurate Cover Song Identification on Short Queries
Deep learning based methods have become a paradigm for cover song identification (CSI) in recent years, where the ByteCover systems have achieved state-of-the-art results on all the mainstream datasets of CSI.
Graph Contrastive Learning with Implicit Augmentations
Existing graph contrastive learning methods rely on augmentation techniques based on random perturbations (e. g., randomly adding or dropping edges and nodes).
BYTECOVER2: TOWARDS DIMENSIONALITY REDUCTION OF LATENT EMBEDDING FOR EFFICIENT COVER SONG IDENTIFICATION
Convolutional neural network (CNN)-based methods have dominated the recent research of cover song identification (CSI).
Ranked #1 on
Cover song identification
on SHS100K-TEST
HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection
To combat these problems, we introduce HTS-AT: an audio transformer with a hierarchical structure to reduce the model size and training time.
Ranked #4 on
Sound Event Detection
on DESED
Zero-shot Audio Source Separation through Query-based Learningfrom Weakly-labeled Data
Our approach uses a single model for source separation of multiple sound types, and relies solely on weakly-labeled data for training.
Zero-shot Audio Source Separation through Query-based Learning from Weakly-labeled Data
Our approach uses a single model for source separation of multiple sound types, and relies solely on weakly-labeled data for training.
Ranked #1 on
Audio Source Separation
on AudioSet
ByteCover: Cover Song Identification via Multi-Loss Training
We present in this paper ByteCover, which is a new feature learning method for cover song identification (CSI).
Ranked #2 on
Cover song identification
on Da-TACOS
Rule-embedded network for audio-visual voice activity detection in live musical video streams
Detecting anchor's voice in live musical streams is an important preprocessing for music and speech signal processing.
Sound Multimedia Audio and Speech Processing
Contrastive Unsupervised Learning for Audio Fingerprinting
The rise of video-sharing platforms has attracted more and more people to shoot videos and upload them to the Internet.
