2 citations · 5 across the 14 of their papers we have counts for
15 papers
MixJudge: Learning a Language-Queryable Critic for Vocal Mixing
Kuan-Hsun Ho, Yuan-Chiao Cheng, Yen-Tung Yeh +1
Mixing requires not only applying processing but also assessing the resulting mix. Audio-language models can provide conversa- tional mixing advice, but existing evaluations do not…
EG-VAE: A Unified Framework for Electric Guitar Tone Transfer and Removal
Yen-Tung Yeh, Yun-Ning, Hung +1
Electric guitar tone transfer (EGTT) and tone removal (EGTR) are two fundamental tasks in guitar tone modeling: EGTT replaces a recording's tone with that of a reference, while EGT…
Rethinking Automatic Music Mixing as Sequential Stem Blending
Yen-Tung Yeh, Chung-Jui Chan, Yun-Ning +2
Automatic music mixing, the task of automatically combining individual audio tracks into a cohesive mixture, is typically addressed by parallelized architectures that process all i…
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…
SynthCloner: Synthesizer-style Audio Transfer via Factorized Codec with ADSR Envelope Control
Jeng-Yue Liu, Ting-Chao Hsu, Yen-Tung Yeh +2
Electronic synthesizer sounds are controlled by parameter settings that yield complex timbral characteristics and ADSR envelopes, making synthesizer-style audio transfer particular…
Fx-Encoder++: Extracting Instrument-Wise Audio Effects Representations from Mixtures
Yen-Tung Yeh, Junghyun Koo, Marco A. Martínez-Ramírez +3
General-purpose audio representations have proven effective across diverse music information retrieval applications, yet their utility in intelligent music production remains limit…
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…
AI TrackMate: Finally, Someone Who Will Give Your Music More Than Just "Sounds Great!"
Yi-Lin Jiang, Chia-Ho Hsiung, Yen-Tung Yeh +2
The rise of "bedroom producers" has democratized music creation, while challenging producers to objectively evaluate their work. To address this, we present AI TrackMate, an LLM-ba…
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…
PyNeuralFx: A Python Package for Neural Audio Effect Modeling
Yen-Tung Yeh, Wen-Yi Hsiao, Yi-Hsuan Yang
We present PyNeuralFx, an open-source Python toolkit designed for research on neural audio effect modeling. The toolkit provides an intuitive framework and offers a comprehensive s…
Hyper Recurrent Neural Network: Condition Mechanisms for Black-box Audio Effect Modeling
Yen-Tung Yeh, Wen-Yi Hsiao, Yi-Hsuan Yang
Recurrent neural networks (RNNs) have demonstrated impressive results for virtual analog modeling of audio effects. These networks process time-domain audio signals using a series…
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…
Exploiting Pre-trained Feature Networks for Generative Adversarial Networks in Audio-domain Loop Generation
Yen-Tung Yeh, Bo-Yu Chen, Yi-Hsuan Yang
While generative adversarial networks (GANs) have been widely used in research on audio generation, the training of a GAN model is known to be unstable, time consuming, and data in…
A Benchmarking Initiative for Audio-Domain Music Generation Using the Freesound Loop Dataset
Tun-Min Hung, Bo-Yu Chen, Yen-Tung Yeh +1
This paper proposes a new benchmark task for generat-ing musical passages in the audio domain by using thedrum loops from the FreeSound Loop Dataset, which arepublicly re-distribut…