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1 24
2 i
3 ii ( [11] ) ConfusionMatrix( )
4 iii (3 )
5 [1] [2] 1.1:
6 1 2 (a) Paro HP (b) ifbot 1.2: [3] [4] ifoo ifbot [5] 1.2 Robot Assisted Activity: RAA [6, 7, 8, 9, 10, 11] 1.2 [6] [8] [9] [11] 1.3
![1 3 1.3: ( [11] ) ( 1.](/docs-images/43/23130494/images/7-0.png "4) [11] [12, 13, 14] 1.")
7 : ( [11] ) ( 1.4) [11] [12, 13, 14] 1.5 WordNet [15] 1.6
![4) [11] [12,](/docs-images/43/23130494/images/page_7.jpg "13, 14] 1.")
8 : [16] [12] 利 者 会 話 型 ロボット 音 声 合 成 エンジン 音 声 認 識 返 答 選 択 生 成 モジュール 認 識 結 果 (テキスト) 話 題 - 返 答 データベース 形 態 素 解 析 (Mecab) 話 題 認 識 モジュール 日 本 語 WordNet (PostgreSQL) 1.5:
9 1 5 梨 果 (synset= n) 果 物 (synset= n) link:hype りんご(synset: n) link:hypo 焼 きりんご(synset: n) link:hype 桃 (synset: n) 上 位 概 念 :hype 下 位 概 念 :hypo (a) WordNet) synset 階 層 の 深 さ, 最 下 位 概 念 を 決 定 階 層 の 深 さ 共 通 上 位 概 念 群 最 下 位 概 念 野 球 注 目 する 抽 出 単 語 ( 名 詞 ) 比 較 (b) 1.6:
10 1 6 2 ( ) [25]
11 (N-gram ) 2.1:
![2 8 2.2: 2.2 2.2 (2.1) [17] p(w X) = p(w ) p(x W ) (2.1) (2.](/docs-images/43/23130494/images/12-0.png "1) X W p(x W ) W p(w) W W w i W = (w 1, w 2,, w n ) p(w i ) p(w ) (2.")
12 : (2.1) [17] p(w X) = p(w ) p(x W ) (2.1) (2.1) X W p(x W ) W p(w) W W w i W = (w 1, w 2,, w n ) p(w i ) p(w ) (2.2) p(w ) = i p(w i ) (2.2) 2 W p(w ) 0
13 2 9 W 2.3 ( 2.1) (ky o u t o) ky o: t o W m M = (m 1, m 2,, m l ) 2.1 p(w X) 2.3 p(x W ) = i p(x m i ) (2.3) (2.3) p(x m i ) X Mel-Frequency Cepstral Coefficients: MFCC [22] [23] 2.3 MFCC Hidden Markov Model HMM
![2 10 2.3: HTK(Hidden Markov Model Toolkit)[24] 2.2 2.](/docs-images/43/23130494/images/14-0.png "2 2.1: a i u e o a: i: u: e: o: k g s z t d n h b p m y r w ky gy sh j ch ts dy")
14 : HTK(Hidden Markov Model Toolkit)[24] : a i u e o a: i: u: e: o: k g s z t d n h b p m y r w ky gy sh j ch ts dy ny f hy by py my ry N q sp
15 : 16[kHz] MFCC+ MFCC+ Pow 39 Hamming 25[ms] 10[ms]
16 [18, 19] [20, 21] 3.2
![[18, 19]](/docs-images/43/23130494/images/page_16.jpg "[20, 21]")
17 : NII-SRC [25] - [26] ATR [26, 27] Julius[29] Confusion Matrix 210 e a 605 Confusion Matrix
![212 2 [26, 27] Julius[29] 0](/docs-images/43/23130494/images/page_17.jpg "3.2 Confusion Matrix 210 e")
18 : ( 208,210,605,619,622,704) wav 24kHz 16bit mono 16kHz Julius PTM 2.1 STEP1 STEP2 STEP3 - Julius STEP2 (Confusion Matrix)
19 3 15 Confusion Matrix (a) 210 (b) : ConfusionMatrix( ) 3.3:
20 : 2 m r(i 1) -m ri m t(i 1) -m ti 3 m r(i 1) -m ri +m r(i+1) m t(i 1) -m ti +m t(i+1) (i=1) m ri +m r(i+1) (i=l) m r(i 1) -m ri m ti +m t(i+1) m t(i 1) -m ti 4 m r(i 2) -m r(i 1) -m ri +m r(i+1) m t(i 2) -m t(i 1) -m ti +m t(i+1) (i=1) m ri +m r(i+1) (i=2) m r(i 1) -m ri +m r(i+1) (i=l) m r(i 2) -m r(i 1) -m ri m ti +m t(i+1) m t(i 1) -m ti +m t(i+1) m t(i 2) -m t(i 1) -m ti R R = (m r1, m r2,, m rl ) T T = (m t1, m t2,, m tl ) R i m ri m ti k (i=1 2) (i=l) ( 3.2),, 1 1 dis
21 :
22 [25, 26] Julius [29] Julius PTM - 1. Julius Confusion Matrix
23 : ( 208,210,605,619,622,704) wav 24kHz 16bit mono Julius PTM Web
24 : (3 ) a-n+o a-m+o 2 a-b+o a-w+o 5 u-k+a u-g+a 1 g+o m+o 3 o-b+u o-m+u 1 r-i+s e-n+s 2 a-k+a a-g+a % : (2.48 ) (18.97 ) (37.01 ) (3.94 ) (25.76 ) (49.45 ) (2.73 ) (28.15 ) (48.40 ) (6.16 ) (26.52 ) (51.92 ) (4.87 ) (32.07 ) (45.39 ) (4.67 ) (25.18 ) (44.72 )
25 : 4.2:
26 : (11.61 ) 210(6.83 ) (10.16 ) 213(9.20 ) (10.74 ) 251(13.42 ) (5.61 ) 594(21.79 ) (7.80 ) 230(11.00 ) (5.93 ) 537(19.66 )
27
28 24
29 25 [1] (2012) ( ) [2] ( ) [3] [4] Paro [5] ifoo [6] Vol. 44 No.11 pp [7] : A1-C24(1) 2010 [8] pp [9] WIT 108(332) pp [10], , 1A1-J03, 2009 [11], Robot Assisted Activity, 6 (FIT2007), 3, pp
30 26 [12] Y.Izutsu, H.Kawanaka, K.Yamamoto, K.Suzuki, H.Takase, S.Tsuruoka : A Study on Convention Content Recognition Using JapaneseWordNet for Robot-Assisted Therapies. Journal of Advanced Computational Intelligence and Intelligent Informatics(JACIII 2012), Vol.16 No.1, pp.62-68, 2012 [13] Y. Izutsu, H. Kawanaka, K. Yamamoto, K. Suzuki H. Takase and S. Tsuruoka, Proposal of Conversation Content Recognition Using Japanese WordNet for Robot- Assisted Therapy, Proc. of the Joint 5th Intl. Conf. on Soft Computing and Intelligent Systems and 11th Intl. Symposium on Advanced Intelligent Systems (SCIS&ISIS2010), pp , 2010 [14] Vol.32 No.2 pp [15] WordNet -A lexical database for English-. Princeton University, [16] 28 pp [17] Julius Vol.20 No.1 pp [18],,, 66 1, pp.18-22, 2010 [19],,. D, J94-D(2), , 2011 [20],,. SP, 94(42), 17-24, 1994 [21],,,. SP, 107(435), 87-91, 2008 [22] S.B.Davis and P.Mermelstein, Comparison of parametric representations for monosyllabic word recognition in countinuously spoken sentences, IEEE Trans. on Speech and Signal Processing, pp , 1980
31 27 [23],,,,. SP, 104(696), 13-18, 2005 [24] S. Young, J.Jansen, J.Odell, D.Ollason, P.Woodland, The HTK Book, Entropic Research Lab, 1995 [25] NII-SRC, [26],,, 48 12, pp [27],,, pp.89-90, 1988 [28], ATR, pp , 1992 [29] Julius,
32 28 (1) 23,Q4-7 (2) 23,IP-03 (3) 24,C5-2
2 HMM HTK[2] 3 left-to-right HMM triphone MLLR 1 CSJ 10 1 : 3 1: GID AM/CSJ-APS/hmmdefs.gz
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Ver.1.0 2004/3/23 : : 1 1 2 2 2.1..................................... 3 2.2..................................... 5 2.3........................... 5 2.4.............................. 7 2.5............................
フリーソフトでつくる音声認識システム ( 第 2 版 ) サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. このサンプルページの内容は, 第 2 版 1 刷発行時のものです.
フリーソフトでつくる音声認識システム ( 第 2 版 ) サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. http://www.morikita.co.jp/books/mid/084712 このサンプルページの内容は, 第 2 版 1 刷発行時のものです. i 2007 10 1 Scilab 2 2017 2 1 2 1 ii 2 web 2007 9 iii
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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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