1 citations · 1 across the 1 of their papers we have counts for
6 papers
MusicTM-Dataset for Joint Representation Learning among Sheet Music, Lyrics, and Musical Audio
Donghuo Zeng, Yi Yu, Keizo Oyama
This work present a music dataset named MusicTM-Dataset, which is utilized in improving the representation learning ability of different types of cross-modal retrieval (CMR). Littl…
Unsupervised Generative Adversarial Alignment Representation for Sheet music, Audio and Lyrics
Donghuo Zeng, Yi Yu, Keizo Oyama
Sheet music, audio, and lyrics are three main modalities during writing a song. In this paper, we propose an unsupervised generative adversarial alignment representation (UGAAR) mo…
Learning Joint Embedding for Cross-Modal Retrieval
Donghuo Zeng
A cross-modal retrieval process is to use a query in one modality to obtain relevant data in another modality. The challenging issue of cross-modal retrieval lies in bridging the h…
Audio-Visual Embedding for Cross-Modal MusicVideo Retrieval through Supervised Deep CCA
Donghuo Zeng, Yi Yu, Keizo Oyama
Deep learning has successfully shown excellent performance in learning joint representations between different data modalities. Unfortunately, little research focuses on cross-moda…
Personalized Music Recommendation with Triplet Network
Haoting Liang, Donghuo Zeng, Yi Yu +1
Since many online music services emerged in recent years so that effective music recommendation systems are desirable. Some common problems in recommendation system like feature re…
Deep Learning of Human Perception in Audio Event Classification
Yi Yu, Samuel Beuret, Donghuo Zeng +1
In this paper, we introduce our recent studies on human perception in audio event classification by different deep learning models. In particular, the pre-trained model VGGish is u…