第22回ロボット聴覚特集 - 奥乃研究室 - 京都大学

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1, ···,N M(k, i) 2 M(k, i) =2∏j=−2,j̸=iM(k + j, i − N )2 MFM N =48 MFM Figure 2 Figure 2 a)c)e) b)d)f) a)c)e) MFM MFM MFM 5 MFT Hidden Markov ModelHMMMFT x S j f(x|S j )L P (l|S j ) N HMM L∑b j (x) =f(x|S j )= P (l|S j )f(x|l, S j )l−1MFT b j (x) MFM M(i) {L∑N}∑b j (x) = P (l|S j )exp M(i)logf(x(i)|l, S j )l−1i−1 HMM HMM Figure 3: HMM MFT CTK Julius[11]CTK HMM Viterbi Julius Julius [14] MFT N-gram Julius 2 HMM Julius CTK 6 4 Figure 3(1) GSS (2) post-filter(3) MFM (4) MFM MFT GSS [12] 8 post-filter GSS post-filter MFM post-filter MFM 104
(3) MFT Julius 7.1 Figure 4: SIG2 Figure 5: Table 1: ATR //////////// arayuru/geNjitsu/o/subete/jibuN/no/ho:/e/nejimage/ta/no/da/ //////// iq/shu:kaN/bakari/nyu:yo:ku/o/shuzai/shi/ta/ ////////// terebi/ge:mu/ya/pasokoN/de/ge:mu/o/shi/te/asobu/MFT MFM 7 SIG2 8 Figure 4Figure 5 4m×5m 0.3 – 0.4 (RT20) SIG2 2m 30 6090 3 ATR 50 3 Table 1 MFCC (1) MFCC Julius (2) Julius HMM 3 4 HMM ATR 503 306 153 1 150 45,000 7.2 ATR 2 ATR 50 400 ATR 2 CSRC7.3 Figure 6 a)b)ATR 30 53.3% 59.5% 60 53.6% 65.0% 90 66.2%73.5% 90 73.5% ATR 30 38.1% 41.8% 60 37.8% 48.6% 90 47.1% 52.8% 90 52.8% MFCC Pentium 4 (2.53 GHz) LinuxPC MFT Julius 315 373 Julius 314 MFT Julius Julius 84%105
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第22回 ロボット聴覚特集 - 奥乃研究室 - 京都大学

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第22回ロボット聴覚特集 - 奥乃研究室 - 京都大学