Taketo Akama

According to our database, Taketo Akama authored at least 28 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Expectation and Acoustic Neural Network Representations Enhance Music Identification from Brain Activity.

Shogo Noguchi, Taketo Akama, Tai Nakamura, Shun Minamikawa, Natalia Polouliakh

CoRR, March, 2026

Interpretable and Perceptually-Aligned Music Similarity with Pretrained Embeddings.

Arhan Vohra, Taketo Akama

CoRR, January, 2026

PF-D2M: A Pose-free Diffusion Model for Universal Dance-to-Music Generation.

Jaekwon Im, Natalia Polouliakh, Taketo Akama

CoRR, January, 2026

Self-supervised restoration of singing voice degraded by pitch shifting using shallow diffusion.

Yunyi Liu, Taketo Akama

CoRR, January, 2026

Towards Realistic Synthetic Data for Automatic Drum Transcription.

Pierfrancesco Melucci, Paolo Merialdo, Taketo Akama

CoRR, January, 2026

2025

Decoding Selective Auditory Attention to Musical Elements in Ecologically Valid Music Listening.

Taketo Akama, Zhuohao Zhang, Tsukasa Nagashima, Takagi Yutaka, Shun Minamikawa, Natalia Polouliakh

CoRR, December, 2025

SSDLabeler: Realistic semi-synthetic data generation for multi-label artifact classification in EEG.

Taketo Akama, Akima Connelly, Shun Minamikawa, Natalia Polouliakh

CoRR, December, 2025

Music Foundation Model as Generic Booster for Music Downstream Tasks.

Wei-Hsiang Liao, Yuhta Takida, Yukara Ikemiya, Zhi Zhong, Chieh-Hsin Lai, Giorgio Fabbro, Kazuki Shimada, Keisuke Toyama, Kin Wai Cheuk, Marco A. Martínez Ramírez, Shusuke Takahashi, Stefan Uhlich, Taketo Akama, Woosung Choi, Yuichiro Koyama, Yuki Mitsufuji

Trans. Mach. Learn. Res., 2025

Naturalistic Music Decoding from EEG Data via Latent Diffusion Models.

Emilian Postolache, Natalia Polouliakh, Hiroaki Kitano, Akima Connelly, Emanuele Rodolà, Luca Cosmo, Taketo Akama

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

2024

Predicting Artificial Neural Network Representations to Learn Recognition Model for Music Identification from Brain Recordings.

Taketo Akama, Zhuohao Zhang, Pengcheng Li, Kotaro Hongo, Hiroaki Kitano, Shun Minamikawa, Natalia Polouliakh

CoRR, 2024

Annotation-Free MIDI-to-Audio Synthesis via Concatenative Synthesis and Generative Refinement.

Osamu Take, Taketo Akama

CoRR, 2024

A Preliminary Investigation on Flexible Singing Voice Synthesis Through Decomposed Framework with Inferrable Features.

Lester Phillip Violeta, Taketo Akama

CoRR, 2024

Naturalistic Music Decoding from EEG Data via Latent Diffusion Models.

Emilian Postolache, Natalia Polouliakh, Hiroaki Kitano, Akima Connelly, Emanuele Rodolà, Taketo Akama

CoRR, 2024

HyperGANStrument: Instrument Sound Synthesis and Editing with Pitch-Invariant Hypernetworks.

Zhe Zhang, Taketo Akama

CoRR, 2024

Music Proofreading With RefinPaint: Where and How to Modify Compositions Given Context.

Pedro Ramoneda, Martín Rocamora, Taketo Akama

Proceedings of the 25th International Society for Music Information Retrieval Conference, 2024

Annotation-Free Automatic Music Transcription with Scalable Synthetic Data and Adversarial Domain Confusion.

Gakusei Sato, Taketo Akama

Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Hyperganstrument: Instrument Sound Synthesis and Editing With Pitch-Invariant Hypernetworks.

Zhe Zhang, Taketo Akama

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Self-supervised Auxiliary Loss for Metric Learning in Music Similarity-based Retrieval and Auto-tagging.

Taketo Akama, Hiroaki Kitano, Katsuhiro Takematsu, Yasushi Miyajima, Natalia Polouliakh

CoRR, 2023

Automatic Piano Transcription With Hierarchical Frequency-Time Transformer.

Keisuke Toyama, Taketo Akama, Yukara Ikemiya, Yuhta Takida, Wei-Hsiang Liao, Yuki Mitsufuji

Proceedings of the 24th International Society for Music Information Retrieval Conference, 2023

GANStrument: Adversarial Instrument Sound Synthesis with Pitch-Invariant Instance Conditioning.

Gaku Narita, Junichi Shimizu, Taketo Akama

Proceedings of the IEEE International Conference on Acoustics, 2023

2021

A Contextual Latent Space Model: Subsequence Modulation in Melodic Sequence.

Taketo Akama

Proceedings of the 22nd International Society for Music Information Retrieval Conference, 2021

Musical Duet Generation with Tree-Structured Variational Autoencoder.

Adam Oudad, Taketo Akama, Hiroaki Saito

Proceedings of the 2nd AI Music Creativity Conference (AIMC 2021), 2021

2020

Connective Fusion: Learning Transformational Joining of Sequences with Application to Melody Creation.

Taketo Akama

Proceedings of the 21th International Society for Music Information Retrieval Conference, 2020

2019

Controlling Symbolic Music Generation based on Concept Learning from Domain Knowledge.

Taketo Akama

Proceedings of the 20th International Society for Music Information Retrieval Conference, 2019

Term Rewriting that Preserves Models in KR-Logic.

Kiyoshi Akama, Ekawit Nantajeewarawat, Taketo Akama

Proceedings of the Intelligent Information and Database Systems - 11th Asian Conference, 2019

Logical Problem Solving Framework.

Kiyoshi Akama, Ekawit Nantajeewarawat, Taketo Akama

Proceedings of the Intelligent Information and Database Systems - 11th Asian Conference, 2019

2018

Side-Change Transformation.

Kiyoshi Akama, Ekawit Nantajeewarawat, Taketo Akama

Proceedings of the 10th International Joint Conference on Knowledge Discovery, 2018

Computation Control by Prioritized ET Rules.

Kiyoshi Akama, Ekawit Nantajeewarawat, Taketo Akama

Proceedings of the 10th International Joint Conference on Knowledge Discovery, 2018