293 citations · 1k across the 72 of their papers we have counts for
8 papers · 1 filter
Score and Lyrics-Free Singing Voice Generation
Jen-Yu Liu, Yu-Hua Chen, Yin-Cheng Yeh +1
Generative models for singing voice have been mostly concerned with the task of ``singing voice synthesis,'' i.e., to produce singing voice waveforms given musical scores and text…
Improving Automatic Jazz Melody Generation by Transfer Learning Techniques
Hsiao-Tzu Hung, Chung-Yang Wang, Yi-Hsuan Yang +1
In this paper, we tackle the problem of transfer learning for Jazz automatic generation. Jazz is one of representative types of music, but the lack of Jazz data in the MIDI format…
Dilated Convolution with Dilated GRU for Music Source Separation
Jen-Yu Liu, Yi-Hsuan Yang
Stacked dilated convolutions used in Wavenet have been shown effective for generating high-quality audios. By replacing pooling/striding with dilation in convolution layers, they c…
Musical Composition Style Transfer via Disentangled Timbre Representations
Yun-Ning Hung, I-Tung Chiang, Yi-An Chen +1
Music creation involves not only composing the different parts (e.g., melody, chords) of a musical work but also arranging/selecting the instruments to play the different parts. Wh…
Demonstration of PerformanceNet: A Convolutional Neural Network Model for Score-to-Audio Music Generation
Yu-Hua Chen, Bryan Wang, Yi-Hsuan Yang
We present in this paper PerformacnceNet, a neural network model we proposed recently to achieve score-to-audio music generation. The model learns to convert a music piece from the…
Collaborative Similarity Embedding for Recommender Systems
Chih-Ming Chen, Chuan-Ju Wang, Ming-Feng Tsai +1
We present collaborative similarity embedding (CSE), a unified framework that exploits comprehensive collaborative relations available in a user-item bipartite graph for representa…
A Minimal Template for Interactive Web-based Demonstrations of Musical Machine Learning
Vibert Thio, Hao-Min Liu, Yin-Cheng Yeh +1
New machine learning algorithms are being developed to solve problems in different areas, including music. Intuitive, accessible, and understandable demonstrations of the newly bui…
On Output Activation Functions for Adversarial Losses: A Theoretical Analysis via Variational Divergence Minimization and An Empirical Study on MNIST Classification
Hao-Wen Dong, Yi-Hsuan Yang
Recent years have seen adversarial losses been applied to many fields. Their applications extend beyond the originally proposed generative modeling to conditional generative and di…