32 citations · 64 across the 16 of their papers we have counts for
16 papers
Explicit Note-Event Tokenization and Pitch-Validity Constrained Decoding for MIDI-to-Tablature Transcription
Ting-Kai Hsu, Wei-Chin Wang, Kai-Xi Hong +1
Guitar tablature transcription predicts the string and fret position for each note so that the resulting tablature reproduces the target musical part. Prior sequence-to-sequence ap…
StemFX: Learning Mixing Style Representations via Autoregressive FX Chain Prediction on Source-Separated Stems
Yuan-Chiao Cheng, Jui-Te Wu, Brian Chen +3
Audio mixing style encompasses the artistic and technical decisions a mix engineer makes, including level balancing, spatialization, and the choice, ordering, and parameterization…
UT-AISTimprt submission for ICME 2026 Grand Challenge on Academic Text-to-Music Generation
Shunsuke Yoshida, Yu-Hua Chen, Satoru Fukayama
This work investigates the effect of batch sampling strategies during training for text-to-audio music generation under low-data and small-scale model settings. This paper describe…
Towards Generalizability to Tone and Content Variations in the Transcription of Amplifier Rendered Electric Guitar Audio
Yu-Hua Chen, Yuan-Chiao Cheng, Yen-Tung Yeh +3
Transcribing electric guitar recordings is challenging due to the scarcity of diverse datasets and the complex tone-related variations introduced by amplifiers, cabinets, and effec…
Demo of Zero-Shot Guitar Amplifier Modelling: Enhancing Modeling with Hyper Neural Networks
Yu-Hua Chen, Yuan-Chiao Cheng, Yen-Tung Yeh +4
Electric guitar tone modeling typically focuses on the non-linear transformation from clean to amplifier-rendered audio. Traditional methods rely on one-to-one mappings, incorporat…
DDSP Guitar Amp: Interpretable Guitar Amplifier Modeling
Yen-Tung Yeh, Yu-Hua Chen, Yuan-Chiao Cheng +4
Neural network models for guitar amplifier emulation, while being effective, often demand high computational cost and lack interpretability. Drawing ideas from physical amplifier d…
Towards zero-shot amplifier modeling: One-to-many amplifier modeling via tone embedding control
Yu-Hua Chen, Yen-Tung Yeh, Yuan-Chiao Cheng +4
Replicating analog device circuits through neural audio effect modeling has garnered increasing interest in recent years. Existing work has predominantly focused on a one-to-one em…
Improving Unsupervised Clean-to-Rendered Guitar Tone Transformation Using GANs and Integrated Unaligned Clean Data
Yu-Hua Chen, Woosung Choi, Wei-Hsiang Liao +5
Recent years have seen increasing interest in applying deep learning methods to the modeling of guitar amplifiers or effect pedals. Existing methods are mainly based on the supervi…
GTR-CTRL: Instrument and Genre Conditioning for Guitar-Focused Music Generation with Transformers
Pedro Sarmento, Adarsh Kumar, Yu-Hua Chen +3
Recently, symbolic music generation with deep learning techniques has witnessed steady improvements. Most works on this topic focus on MIDI representations, but less attention has…
towards automatic transcription of polyphonic electric guitar music:a new dataset and a multi-loss transformer model
Yu-Hua Chen, Wen-Yi Hsiao, Tsu-Kuang Hsieh +2
In this paper, we propose a new dataset named EGDB, that con-tains transcriptions of the electric guitar performance of 240 tab-latures rendered with different tones. Moreover, we…
Source Separation-based Data Augmentation for Improved Joint Beat and Downbeat Tracking
Ching-Yu Chiu, Joann Ching, Wen-Yi Hsiao +3
Due to advances in deep learning, the performance of automatic beat and downbeat tracking in musical audio signals has seen great improvement in recent years. In training such deep…
Automatic Composition of Guitar Tabs by Transformers and Groove Modeling
Yu-Hua Chen, Yu-Hsiang Huang, Wen-Yi Hsiao +1
Deep learning algorithms are increasingly developed for learning to compose music in the form of MIDI files. However, whether such algorithms work well for composing guitar tabs, w…
Unconditional Audio Generation with Generative Adversarial Networks and Cycle Regularization
Jen-Yu Liu, Yu-Hua Chen, Yin-Cheng Yeh +1
In a recent paper, we have presented a generative adversarial network (GAN)-based model for unconditional generation of the mel-spectrograms of singing voices. As the generator of…
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…
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…
Dixit: Interactive Visual Storytelling via Term Manipulation
Chao-Chun Hsu, Yu-Hua Chen, Zi-Yuan Chen +3
In this paper, we introduce Dixit, an interactive visual storytelling system that the user interacts with iteratively to compose a short story for a photo sequence. The user initia…