Web Web Summary Communication robots start to become deep relationship to people s lives by the development of robotics. However, it is difficult for
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- しょうじ いせき
- 5 years ago
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1 No. 179 Web Manzai Robots: Automatic Generation of Manzai Scenario from Web News
2 Web Web Summary Communication robots start to become deep relationship to people s lives by the development of robotics. However, it is difficult for robots to communicate smoothly with people. We have proposed a system that generates humorous dialogue scenarios automatically to Manzai robots aiming at that people to communicate smoothly with robots. In this thesis, we improve automatic generation system to advance the funny and understandability. In improvement of funny, we propose sentiment mistake gaps. Futuremore we propose the method of automatic generation of paraphrasing sentences from web news that user support of understanding of news articles.
3 XML
4 xml (2) (5)-(8) TVML CG CG CG
5 t CG t
6 Pepper 2 Pepper [1] [2] Web Web Web Web Web Web https:// pdf 2 Pepper 1
7 1: [3] (1) 1 (2) Web Web A A B Web
8 2 [4] 2 [5][6] 2 1 [7] Souneil[8] NewsCube Media Bias [9] Web [10] [11] [12] SVO [13] Web Chambers [14] Stress@Work Johan[15] Twitter Tweet Nakamura[16] 3
9 [17] [18]N [19] Web [20] Web Web [21] Web 1 Yahoo! URL 1: 3 Yahoo! Japan 4
10 2: XML cm 52cm 60cm 55cm 50cm 50cm 2 PC LAN 2 PC
11 図 3: 漫才ロボットあいちゃん 左 とゴン太 右 図 4: 感情に合わせたロボットの表情 ため モーターでの回転動作でツッコミの動作を表現する 目の表情は 2 つの有機 EL ディス プレイに図 4 のような画像を移すことで表現する 画像の種類は 50 種類あり 台本に合わせた 様々な感情を表現することが可能である 4 漫才台本自動生成 漫才台本自動生成にあたり 台本をある程度形式化する必要がある 本論文では灘本ら [22] が提案した漫才台本自動生成の枠組みを使用し 漫才台本をつかみ 本ネタ オチに分割した 三段構成の流れでの漫才台本の生成を行う また 種々ある漫才スタイルのうち しゃべくり 漫才 と呼ばれる話芸のみで統一されたボケ役とツッコミ役の 2 体のロボットの対話形式で行 う つかみ 本ネタ オチの役割の概要および各部で本提案システムが自動生成するボケを表 2 に示す 4.1 XML 形式の漫才台本 お題を ノーベル賞 とした時に 提案手法により出力する漫才台本図 5 に示す 本論文で用 いる漫才台本はロボットが内容を処理しやすいように xml のファイル形式で出力する 漫才台 本には台詞以外に細かい動きや表情の変化等を記述し タグによる命令処理を 1 行毎に上から 下に台本を読み込んで実行し 漫才ロボットによる漫才を実演する タグ中の cast が発話 look が回転動作による視点移動 PEmo が表情の変化の命令処理を表し 命令対象は A があいちゃん G をゴン太でそれぞれ指定する 例えば 図 5 の <cast name= A >どもー 6
12 2: </cast> <look name= G, what= A /> <look name= G, what= audience /> <PEmo name= G >PE47/> 47 1 </script> ) [23] 7
13 5: xml <cast name= A > </cast> <PEmo name= A >PE44/> (1) 8
14 6: E j i = 2(E i 0.5) (1) E j i j i 3 : (1) : (1)
![7: 5 1 [2] 7 4.3.](/docs-images/91/106664529/images/15-0.jpg "1 7 - - (denryoku), (kenryoku) Wikipedia Wikipedia [24]")
15 7: 5 1 [2] (denryoku), (kenryoku) Wikipedia Wikipedia [24] 1 1 [25] Grice[26] Wikipedia 4 [26] 1 10
16 : 1st adjective 2nd adjective 3rd adjective
17 1 Wikipedia Sta(s i ) (2) Sta(s i ) = 1 log n N (2) s i n N N 2,931,465 e i Rel(e i ) (3) Rel(e i ) = n n i=0 Sta(s i ) (3) 2 Web (4) Con(key,e i ) = 1 log Cog(key) Cog(e i) max(cog(key),cog(e i )) Cog(key) Cog(e i ) Con(key,e i ) 1 Con(key,e i ) 0 (3) Rel(e i ) (4) Con(key,e i ) 5 (4)
18 5: 8: A A e 3. A A e 4. A B
19 A (1) 8 (2) 3 2 A A A e A B A e B B A e A A B A B B B A A A e 8 A A B 8 A B 14
20 9: X Y Z Z Z Z X Y Z Z 4 1. X 2. X X Z 3. Z Z 4. Z Y X X 15
21 X 9 X X Z Z X X Z Z Z Z Z Z (jusyou) (buturi) (gakusyou) (gakusyou) Z Z Y Z X Z X Z Z Y Y 5 Web Web / / S O V S O 16
22 10: Web S 1 O 1 V 1 6: S 0 O 0 S 1 O 1 V Web / / S O V S O V S 0 O 0 V 0 S 0 O 0 V 0 S O V S 1 O 1 V 1 17
23 S 1 O 1 S 0 S 1 O 0 O 1 V 0 V 1 S 1 O 1 V 1 6 S 0 O 0 V 0 S 1 O 1 V PageRank [27] PageRank Web Web PageRank PageRank t i Wikipedia W i (5) t i PR(t i ) PR(t i ) = (1 d) + d n PR(P j ) j=1 C(P j ) (5) n W i C(P j ) W i P j PR(P j ) W i j d
24 Wikipedia PR(t i ) t i Wikipedia t i Wikipedia t i Val(t i ) (6) Val(t i ) = PR(t i ) + logt D(t i ) (6) PR(t i ) 1 Wikipedia PageRank t i T D(t i ) 2 t i 2 Val(t i ) t i T Web 2. Web S 0 O 0 V 0 3. S 1 4. O 1 5. V 1 6. S 1 O 1 V 1 P
25 11: 20
26 IT 1 T S 0 O 0 V 0 Web CaboCha 6 S 0 O 0 V 0 S 1 O 1 V 1 S 1 O 1 V 1 Web S 1 O 1 V 1 7: Val(t i ) (Val(t i )) : Val(t i ) (Val(t i )) S 1 S 1 1. S 0 S 0 S 0 Wikipedia S 0 S 0i S 0 S 0i 2. S 1 S 1 j S 1 S 1 j T Wikipedia T 3. S 1 j S 1 j 6 taku/software/cabocha/ 21
27 4. S 1 S 0 S 1 S 0i (i = 1,...,n) S 1 j ( j = 1,...,m) S 1 7 S 0i 8 S 1 7 Val(t i ) S 1 j S 1 O 1 O 1 O 0 O 1 S 1 O 1 O 1 O 1l S 1 S 1 S 1 O 1l O 0 O 0k O 1l O 1 1. O 0. O 0 S 0 O 0 O 0k 2. O 1 O 1l S 1 S Wikipedia O 1 3. O 1l O 1l 4. O 1 O 0 O 1l O 1 O 0 S 1 O 1 O 1l O 1l ATP Val(t i ) O 1 j O 1 V 1 V 1 S 1 O
28 12: S 1 O 1 V 1 S 1 O 1 V 1 S 1 O 1 V 1 S 0 O 0 V 0 P P T Web
29 図 13: 図 12(2) の記事に対してシステムが自動生成した漫才台本 24
30 1 3 12(1) ) 12(2) ) 2 13 (1) (2) (3) (4) (5) (6) (7) (8) 2 (1) (2) (3) (4) (5) (6) (7) (8) (1) (2)
31 14: (3) (4) 15 (5) (3)
32 15: 16 (6) 4 8 (7) 3.6 (8) 3.9 (8) 2 (5) (6) 6.2 Web Web 2 27
33 16: (5)-(8) Web 2 Web Web (1) (2) 28
34 17: (3) (4) 3 (4) (4) 5 (1)-(3) 19 t 9 9 t(25)=2.208, p.05 t(27)=5.827,p.05 t(29)=5.395,p.05 Web Web Web (4) 20 (4) (4) Web Web 29
35 図 18: 図 17 の記事に対してシステムが自動生成した漫才台本 30
36 19: 2 2 (4)
37 9: t Mean SD t DF p (M) (N) (M) (N) (M) (N) (M:, N: ) 20: 6.3 NHK TVML( Television Making Language ) [28] TVML CG CG TVML 2 CG 2 CG TVML CG CG CG TVML CG 3 32
38 図 21: TVML による CG キャラクターのイメージ. は 19 インチのモニターに漫才の実演映像を流した CG キャラクターのイメージを図 21 に示 す 被験者は 先の漫才ロボットとニュースを読むロボットとの比較実験を行った 18 人であり CG キャラクターの漫才を観察後 以下の評価項目に 5 段階 5 高 1 低 で評価を行う (5) CG キャラクターの漫才はわかりやすかったか (6) CG キャラクターの漫才はおもしろかったか (7) CG キャラクターの漫才は親しみやすかったか (8) 漫才ロボットの漫才と CG キャラクターの漫才ではどちらが好きか 評価指標には 漫才ロボットの漫才と同様の評価指標を用い 先の実験の漫才ロボットの漫才 との結果と比較を行う 評価項目 (8) では 漫才ロボットの漫才が CG キャラクターの漫才と比 較して総合的にどの程度の有意性があるかを検証する なお この質問項目 5 段階評価ではな く 3 択 1 漫才ロボットの漫才 2 CG キャラクター 3 どちらとも言えない での評価を 行う 表 10: 漫才ロボットと CG キャラクターの評価結果の t 検定 Mean わかりやすさ (M) わかりやすさ (C) おもしろさ (M) 3.88 おもしろさ (C) 3.66 親しみやすさ (M) 3.88 親しみやすさ (C) 3.05 SD t DF p (M:漫才ロボット, C:CG キャラクター) 33
39 22: CG (5)-(7) 23 (8) 23 CG t t(33)=0.796,p.05 t(32)=0.978,p.05 t(26)=2.931,p.05 CG CG CG CG CG 4 3 (8) 7 CG 4 CG CG CG CG 34
40 23: CG CG TVML CG (8) CG 3 2 CG 7 Web Web 35
41 PageRank Wikipedia Wikipedia 8 9 ARG 4 Web pp , Web 7 Web (WebDB Forum 2014) CD-ROM, 8pages, (DEIM2015) F4-4, 8 pages, Web DE
42 Web 8 (DEIM2016) 2016(to appear). Web ARG 6 Web 2015.,,,,,,,, Vol. 8, No. 1, pp. 9-18, Web 7 Web (WebDB Forum 2014) (DEIM2015) Web 8 (DEIM2016) 2016(to appear) A1-T02, 3 pages (DVD-ROM), Raspberry Pi A1-J01, 3 pages (DVD-ROM), XML 16 pp , Ryo Mashimo, Tomohiro Umetani, Tatsuya Kitamura and Akiyo Nadamoto, Generating Funny Dialogue between Robots based on Japanese Traditional Comedy Entertainment, In Proceedings of the 2014 Conference on Interactive Entertainment(IE2014), December 2-3, Australia, Newcastle, ACM, pp ,
43 Ryo Mashimo, Tomohiro Umetani, Tatsuya Kitamura and Akiyo Nadamoto, Automatic Generation of Japanese Traditional Funny Scenario from Web Content based on Web Intelligence, The 17th International Conference on Information Integration and Web-based Applications & Services (iiwas2015), December 11-13, Brussels, Belgium, pp , Ryo Mashimo, Tomohiro Umetani, Tatsuya Kitamura and Akiyo Nadamoto, Human-Robots Implicit Communication based on Dialogue between Robots using Automatic Generation of Funny Scenarios from Web, In Proceedings of the 11th ACM/IEEE International Conference on Human-Robot Interaction(HRI 2016), March 7-10, Christchurch, New Zealand, 2016(to appear). Tomohiro Umetani, Satoshi Aoki, Kazuhiro Akiyama, Ryo Mashimo, Tatsuya Kitamura and Akiyo Nadamoto, Manzai Robot System with Scalability based on Distributed Software Components, in Proceedings of the 26th 2015 International Symposium on Micro-Nano Mechatronics and Human Science(MHS2015), November 23-25, Nagoya, Japan, pp , Journal Tomohiro Umetani, Ryo Mashimo, Akiyo Nadamoto, Tatsuya Kitamura and Hirotaka Nakayama, Manzai Robots: Entertainment Robots based on Auto-created Manzai Scripts from Web News Articles, Journal of Robotics and Mechatronics, Vol. 26, No. 5, pp , Web 7 Web (WebDB Forum 2014) CD-ROM, 8pages, Web XML 16 9 RT
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36 知能と情報知能と情報 ( 日本知能情報ファジィ学会誌 ( ))Vol.29, No.6, pp.226-230(2017) 会告 Zadeh( ザデー ) 先生を偲ぶ会 のご案内 Zadeh( ) とと と 日 2018 1 20 日 ( ) 15:00 17:30(14:30 18:00 ) 2F ( ) 530-8310 1-1-35 TEL: 06-6372-5101 https://www.hankyu-hotel.com/hotel/osakashh/index.html
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