Search Results for author:
Found 7 papers, 4 papers with code
ImprovNet: Generating Controllable Musical Improvisations with Iterative Corruption Refinement
However, in the realm of symbolic music, generating controllable and expressive performance-level style transfers for complete musical works remains challenging due to limited datasets, especially for genres such as jazz, and the lack of unified models that can handle multiple music generation tasks.
YourMT3+: Multi-instrument Music Transcription with Enhanced Transformer Architectures and Cross-dataset Stem Augmentation
Further testing on pop music recordings highlights the limitations of current models.
Ranked #1 on
Multi-instrument Music Transcription
on URMP
(using extra training data)
Offline Clustering Approach to Self-supervised Learning for Class-imbalanced Image Data
Class-imbalanced datasets are known to cause the problem of model being biased towards the majority classes.
Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrastive Learning
Most of existing audio fingerprinting systems have limitations to be used for high-specific audio retrieval at scale.
Sequential Skip Prediction with Few-shot in Streamed Music Contents
This paper provides an outline of the algorithms submitted for the WSDM Cup 2019 Spotify Sequential Skip Prediction Challenge (team name: mimbres).
Ranked #1 on
Sequential skip prediction
on MSSD
Audio Cover Song Identification using Convolutional Neural Network
To do this, we first build the CNN using as an input a cross-similarity matrix generated from a pair of songs.
Lyrics-to-Audio Alignment by Unsupervised Discovery of Repetitive Patterns in Vowel Acoustics
Most of the previous approaches to lyrics-to-audio alignment used a pre-developed automatic speech recognition (ASR) system that innately suffered from several difficulties to adapt the speech model to individual singers.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
