Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Ikemiya, Yukara"'
Autor:
Chae, Yunkee, Choi, Woosung, Takida, Yuhta, Koo, Junghyun, Ikemiya, Yukara, Zhong, Zhi, Cheuk, Kin Wai, Martínez-Ramírez, Marco A., Lee, Kyogu, Liao, Wei-Hsiang, Mitsufuji, Yuki
Recent state-of-the-art neural audio compression models have progressively adopted residual vector quantization (RVQ). Despite this success, these models employ a fixed number of codebooks per frame, which can be suboptimal in terms of rate-distortio
Externí odkaz:
http://arxiv.org/abs/2410.06016
Autor:
Comunità, Marco, Zhong, Zhi, Takahashi, Akira, Yang, Shiqi, Zhao, Mengjie, Saito, Koichi, Ikemiya, Yukara, Shibuya, Takashi, Takahashi, Shusuke, Mitsufuji, Yuki
Recent advances in generative models that iteratively synthesize audio clips sparked great success to text-to-audio synthesis (TTA), but with the cost of slow synthesis speed and heavy computation. Although there have been attempts to accelerate the
Externí odkaz:
http://arxiv.org/abs/2406.17672
Autor:
Zhang, Yixiao, Ikemiya, Yukara, Choi, Woosung, Murata, Naoki, Martínez-Ramírez, Marco A., Lin, Liwei, Xia, Gus, Liao, Wei-Hsiang, Mitsufuji, Yuki, Dixon, Simon
Recent advances in text-to-music editing, which employ text queries to modify music (e.g.\ by changing its style or adjusting instrumental components), present unique challenges and opportunities for AI-assisted music creation. Previous approaches in
Externí odkaz:
http://arxiv.org/abs/2405.18386
Autor:
Zhang, Yixiao, Ikemiya, Yukara, Xia, Gus, Murata, Naoki, Martínez-Ramírez, Marco A., Liao, Wei-Hsiang, Mitsufuji, Yuki, Dixon, Simon
Recent advances in text-to-music generation models have opened new avenues in musical creativity. However, music generation usually involves iterative refinements, and how to edit the generated music remains a significant challenge. This paper introd
Externí odkaz:
http://arxiv.org/abs/2402.06178
Autor:
Takida, Yuhta, Ikemiya, Yukara, Shibuya, Takashi, Shimada, Kazuki, Choi, Woosung, Lai, Chieh-Hsin, Murata, Naoki, Uesaka, Toshimitsu, Uchida, Kengo, Liao, Wei-Hsiang, Mitsufuji, Yuki
Vector quantization (VQ) is a technique to deterministically learn features with discrete codebook representations. It is commonly performed with a variational autoencoding model, VQ-VAE, which can be further extended to hierarchical structures for m
Externí odkaz:
http://arxiv.org/abs/2401.00365
Autor:
Toyama, Keisuke, Akama, Taketo, Ikemiya, Yukara, Takida, Yuhta, Liao, Wei-Hsiang, Mitsufuji, Yuki
Taking long-term spectral and temporal dependencies into account is essential for automatic piano transcription. This is especially helpful when determining the precise onset and offset for each note in the polyphonic piano content. In this case, we
Externí odkaz:
http://arxiv.org/abs/2307.04305
This paper presents a new method of singing voice analysis that performs mutually-dependent singing voice separation and vocal fundamental frequency (F0) estimation. Vocal F0 estimation is considered to become easier if singing voices can be separate
Externí odkaz:
http://arxiv.org/abs/1604.00192
Publikováno v:
2015 IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP); 2015, p574-578, 5p
Publikováno v:
2015 IEEE/RSJ International Conference on Intelligent Robots & Systems (IROS); 2015, p5555-5560, 6p
Publikováno v:
2014 IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP); 2014, p3127-3131, 5p