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20152023
most citedThe Jazz Transformer on the Front Line: Exploring the Shortcomings of AI-composed Music through Quantitative Measures

38 citations · 298 across the 42 of their papers we have counts for

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Showing 2018Show all

17 papers · 1 filter

cs.SD2018

Learning to match transient sound events using attentional similarity for few-shot sound recognition

Szu-Yu Chou, Kai-Hsiang Cheng, Jyh-Shing Roger Jang +1

In this paper, we introduce a novel attentional similarity module for the problem of few-shot sound recognition. Given a few examples of an unseen sound event, a classifier must be…

cs.SD2018

PerformanceNet: Score-to-Audio Music Generation with Multi-Band Convolutional Residual Network

Bryan Wang, Yi-Hsuan Yang

Music creation is typically composed of two parts: composing the musical score, and then performing the score with instruments to make sounds. While recent work has made much progr…

cs.SD2018

Learning Disentangled Representations for Timber and Pitch in Music Audio

Yun-Ning Hung, Yi-An Chen, Yi-Hsuan Yang

Timbre and pitch are the two main perceptual properties of musical sounds. Depending on the target applications, we sometimes prefer to focus on one of them, while reducing the eff…

cs.SD2018

Multitask learning for frame-level instrument recognition

Yun-Ning Hung, Yi-An Chen, Yi-Hsuan Yang

For many music analysis problems, we need to know the presence of instruments for each time frame in a multi-instrument musical piece. However, such a frame-level instrument recogn…

cs.LG2018

Training Generative Adversarial Networks with Binary Neurons by End-to-end Backpropagation

Hao-Wen Dong, Yi-Hsuan Yang

We propose the BinaryGAN, a novel generative adversarial network (GAN) that uses binary neurons at the output layer of the generator. We employ the sigmoid-adjusted straight-throug…

eess.AS2018

A Streamlined Encoder/Decoder Architecture for Melody Extraction

Tsung-Han Hsieh, Li Su, Yi-Hsuan Yang

Melody extraction in polyphonic musical audio is important for music signal processing. In this paper, we propose a novel streamlined encoder/decoder network that is designed for t…