第120回 音楽情報科学研究会(夏のシンポジウム) 参加案内

プログラム

(2018/8/20）

第28回GMIワークショップ（GANに基づく音楽生成特集）

2018/8/21

13:00-14:00 【和声付け】

14:10-15:10 【招待講演】

16:30-16:45 【デモセッション】

16:45-18:00 【デモセッション】

18:00-19:00 (広島工業大学 学内見学ツアー）

19:00-21:00 【懇親会】

2018/8/22

9:15-10:45　【深層学習】（4件）

11:00-12:00　【実験】　（2件）

12:00-13:00

13:00-15:00【作曲・編曲】（4件）

15:15-16:15【演奏解析・追跡】（2件）

16:30-18:00 【特別企画】

2018/8/23

9:00-10:00　【音源分離・楽譜】（2件）

10:15-11:45　【音楽演奏】（3件）

11:45-12:15

(13:00-15:00)

招待講演の詳細

• 藤永 一郎 先生 (McGill University, Canada) [web] 「The Art of Teaching Computers: The SIMSSA Optical Music Recognition Workflow」Abstract: In many machine learning systems it would be effective to create a pedagogical environment where both the machines and the humans can incrementally learn to solve problems through interaction and adaptation. We are designing an optical music recognition workflow system where human operators can intervene to correct and teach the system at certain stages so that both parties can learn from the errors and, consequently, the overall performance is increased progressively as more music scores are processed.
• Dr. Yi-Hsuan Yang (Academia Sinica, Taiwan) [web] 「Machine Learning for Creative AI Applications in Music」Abstract: In this talk, I will briefly introduce three latest projects in our lab at Academia Sinica on creative applications in music, including the singing voice separation project, GenMusic (music generation) project, and the DJnet project. The first project is about separating the singing voice from the musical accompaniments, which can be used as a pre-processing step for many music related applications. The second project is about learning from massive collection of MIDI files to generate multi-track music by a generative adversarial network (GAN). The generative model can be used for generating music either from scratch, or by accompanying a given (instrument) track. The third project is about creating an AI DJ that knows how to manipulate, sample, and sequence musical pieces to create a personalized playlist. The goal of these projects is to enrich the way people create and interact with music in their daily lives, using the latest machine learning (deep learning) techniques.Bio: Yi-Hsuan Yang is an Associate Research Fellow with Academia Sinica. He received his Ph.D. degree in Communication Engineering from National Taiwan University in 2010. He is also a Joint-Appointment Associate Professor with the National Cheng Kung University, Taiwan. His research interests include music information retrieval, affective computing, multimedia, and machine learning. Dr. Yang was a recipient of the 2011 IEEE Signal Processing Society Young Author Best Paper Award, the 2012 ACM Multimedia Grand Challenge First Prize, the 2014 Ta-You Wu Memorial Research Award of the Ministry of Science and Technology, Taiwan, and the 2015 Best Conference Paper Award of the IEEE Multimedia Communications Technical Committee. He is an author of the book Music Emotion Recognition (CRC Press 2011). In 2014, he served as a Technical Program Co-Chair of the International Society for Music Information Retrieval Conference (ISMIR). In 2016, he started his term as an Associate Editor for the IEEE Transactions on Affective Computing and the IEEE Transactions on Multimedia. Dr. Yang is a senior member of the IEEE.

GMIワークショップについて (8/20) について

研究会の前日8/20(月)には、第28回GMIワークショップが同じ会場で開催されます。
聴講のみの参加も可能ですので、音楽生成研究に興味をお持ちの方は、お気軽にご参加ください。

第28回GMIワークショップ（GANに基づく音楽生成特集）

日時：2018年8月20日（月）10:00-18:00
場所：広島工業大学 五日市キャンパス 講義棟「三宅の森 Nexus21」10階スカイテリア
講演・議論に用いる言語：主に英語
参加申し込み：https://docs.google.com/forms/d/e/1FAIpQLSfZET2P5Eu9Rmw1dPyXCk33Jh6BTnjS94lAmAYBz_9jHiu2vA/viewform

GMIの趣旨・活動内容についてはこちらを御覧ください．

今回はGAN: Generative Adversarial Network（敵対的生成ネットワーク）を用いた音楽生成に焦点をあて、そのアプローチで顕著な成果を挙げているYi-Hsuan Yang博士（中央研究院）率いる研究グループのメンバーを招いて開催します。音楽生成研究に興味がある方はもちろん、近年機械学習分野で研究の盛んなGANに興味がある方まで、皆様の参加をお待ちしております。

広島工業大学 学内見学ツアー (8/23) について

8/23の学内見学ツアーはプログラム編成の都合上　8/21の18:00-19:00に移動しました。