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HMM Λ༻͍ͨ೔ຊਓӳ‫ޠ‬Ի੠߹੒ʹ͓͚Δ࿩ऀੑΛอ࣋ͨ͠ӆ཯ิਖ਼େౡ༔࢘†ߴಓ৻೭հ†‫ ాށ‬ஐ‫†ج‬தଜGraham ɹ Neubig†

Sakriani ɹ Sakti†఩†† ಸྑઌ୺Պֶٕज़େֶӃେֶ ৘ใՊֶ‫ڀݚ‬Պ˟ 630–0192 ಸྑ‫ݝ‬ੜۨࢢߴࢁொ 8916–5
E-mail: †{oshima.yuji.ok0,shinnosuke-t,tomoki,neubig,ssakti,s-nakamura}@is.naist.jp͋Β·͠೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀੑΛ൓өͨ͠ӳ‫ޠ‬Ի੠߹੒༻Ի‫ڹ‬ϞσϧΛߏங͢ΔͨΊʹ͸ɼ೔ຊਓӳ‫ޠ‬ʢERJ:English Read by Japaneseʣʹ‫·ؚ‬ΕΔ࿩ऀੑΛ࠷େ‫͢༻׆ʹݶ‬Δ࿮૊Έ͕༗ޮͰ͋Δͱߟ͑ΒΕΔɽ͔͠͠ͳ͕Βɼ೔ຊਓӳ‫ޠ‬ͷར༻ʹΑΓɼ‫ޠݴ‬ମ‫ܥ‬ͷҧ͍ʹ‫ى‬Ҽ͢Δ೔ӳؒͷӆ཯ͷ૬ҧ΍ൃԻ‫ޡ‬ΓͷӨ‫ڹ‬Λ‫͘ڧ‬ड͚ΔͨΊɼࣗવੑ͕େ͖͘ྼԽ͢Δͱ͍͏໰୊͕ੜ͡Δɽ͜Εʹର͠ຊใࠂͰ͸ɼओʹӆ཯ͷ૬ҧʹண໨͠ɼӳ‫ޠ‬฼‫ޠ‬࿩ऀͷӆ཯Λ༻͍ͯ೔ຊਓӳ‫ޠ‬Ի੠ͷӆ཯Λิਖ਼͢Δ͜ͱͰɼ೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀੑΛอ࣋ͨ͠··ɼΑΓࣗવͳӳ‫ޠ‬Ի੠Λ߹੒͢Δख๏ΛఏҊ͢ΔɽHMM Ի੠߹੒ʹ͓͚ΔϞσϧదԠ๏ΛԠ༻͢Δ͜ͱͰɼӳ‫ޠ‬฼‫ޠ‬࿩ऀͷ‫ܧ‬ଓ௕ͱύϫʔͷಛ௃Λɼ೔ຊਓӳ‫ޠ‬ͷ߹੒Ի੠ʹ൓өͤ͞Δɽ࣮‫ݧ‬తධՁ݁Ռ͔ΒɼఏҊ๏ʹΑΓɼ೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀੑΛอ࣋ͭͭ͠ɼΑΓࣗવੑͷߴ͍ӳ‫ޠ‬Ի੠Λ߹੒Ͱ͖Δ͜ͱΛࣔ͢ɽΩʔϫʔυ೔ຊਓӳ‫ޠ‬ɼHMM Ի੠߹੒ɼӆ཯ิਖ਼ɼ࿩ऀੑɼϞσϧదԠProsody Correction Preserving Speaker Individuality in
English-Read-By-Japanese Speech Synthesis Based on HMM
Yuji OSHIMA† , Shinnosuke TAKAMICHI† , Tomoki TODA† , Graham NEUBIG† , Sakriani
SAKTI† , and Satoshi NAKAMURA†† Graduate School of Information Science, Nara Institute of Science and Technology,
Tatayama-cho 8916–5, Ikoma, Nara, 630–0192 Japan
E-mail: †{oshima.yuji.ok0,shinnosuke-t,tomoki,neubig,ssakti,s-nakamura}@is.naist.jp
Abstract To build an English acoustic model that well captures speaker individuality of each Japanese speaker, aframework using English-Read-by-Japanese (ERJ) voices is eﬀective as it enables to directly model speaker-dependent acoustic characteristics. However, naturalness of English speech synthesized by such an ERJ acoustic model
is signiﬁcantly degraded as it is directly aﬀected by prosodic diﬀerences and pronunciation errors often caused by
diﬀerences of a language system between Japanese and English. To synthesize more natural English speech while
preserving speaker individuality of individual Japanese speakers, we propose a technique to correct prosody of ERJ
voices based on that of a native English speaker. The duration and power of the native English speaker are eﬀectively used to develop the ERJ acoustic model for each Japanese speaker by using model adaptation techniques inHMM-based speech synthesis. The experimental results show that our proposed method is capable of signiﬁcantly
improving naturalness of ERJ synthetic speech while preserving its speaker individuality.
Key words English-Read-by-Japanese (ERJ), HMM-based speech synthesis, prosody correction, speaker individuality, model adaptation—1—This article is a technical report without peer review, and its polished and/or extended version may be published elsewhere.

Copyright ©2014 by IEICE

1. · ͑ ͕ ͖৘ใ௨৴ٕज़΍ަ௨ͷൃୡʹ൐ͬͯɼ‫ٸ‬଎ͳࠃࡍԽ͕ਐΈɼԻ੠߹੒ͷଟ‫ޠݴ‬Խͷधཁ͕૿Ճ͍ͯ͠Δɽۙ೥Ͱ͸ɼΑΓॊೈͳଟ‫ޠݴ‬Ի੠߹੒ͷ࣮‫ݱ‬Λ໨ࢦͯ͠ɼΫϩεϦϯΨϧԻ੠߹੒ͷ‫͕ڀݚ‬੝ΜʹߦΘΕ͍ͯΔ [1]ɽΫϩεϦϯΨϧԻ੠߹੒͸ɼ͋Δ‫ޠݴ‬ͷൃ࿩ऀͷ࿩ऀੑΛҟ‫ޠݴ‬ͷ߹੒Ի੠ʹ൓өͤ͞Δٕज़Ͱ͋Γɼ࿩ऀੑʹΑΔ৘ใ‫ݯ‬ͷಛఆΛଅ͠ɼԁ‫ͳ׈‬ίϛϡχέʔγϣϯΛଅਐ͢Δ໾ׂΛ୲͏ɽಛʹ೔ຊͰ͸ɼ೔ӳؒʹ͓͚Δ߹੒ٕज़ͷधཁ͕ߴ͘ɼԠ༻ྫͱͯ͠͸ɼൃ࿩ऀࣗ਎ͷ੠Ͱ຋༁Ͱ͖ΔԻ੠຋༁γεςϜɼ੠༏ຊਓͷ੠Ͱͷਧ͖ସ͑өըɼࣗ਎ͷ੠Λฉ͖ͳ͕ΒൃԻ࿅श͕Մೳͳ CALL γ

ਤ1HMM Ի੠߹੒ʹ͓͚ΔϞσϧదԠFig. 1 Model adaptation in HMM-based speech synthesis.

εςϜͳͲ͕ߟ͑ΒΕΔɽ͜Ε·Ͱʹɼ౷‫ܭ‬త੠࣭ม‫ٕ׵‬ज़ [2] ΍ӅΕϚϧίϑϞσϧ໨తͱ͠ɼ೔ຊਓӳ‫ޠ‬Ի੠ͷ࿩ऀੑΛอ࣋͠ͳ͕ΒࣗવੑΛվ

ʢHMM: Hidden Markov Modelʣʹ‫ͮ͘ج‬Ի੠߹੒ٕज़ [3] ʹળ͢Δख๏ͱͯ͠ɼHMM Ի੠߹੒ʹ͓͚ΔϞσϧదԠٕज़Λ͓͚Δ࿩ऀదԠٕज़ [4] ʹ͓͍ͯɼӳ‫ޠ‬Λ฼‫͢ͱޠ‬Δ࿩ऀͷԻ༻͍ͨ೔ຊਓӳ‫ޠ‬ͷӆ཯ิਖ਼๏ΛఏҊ͢ΔɽఏҊ๏Ͱ͸ɼӳ‫ޠ‬੠ʹରͯ͠ɼόΠϦϯΨϧԻ੠΍೔ຊ‫ޠ‬Ի੠ͱ͍ͬͨࣗવੑͷ฼‫ޠ‬࿩ऀͷ HMM ʹର͠ɼ೔ຊਓӳ‫ޠ‬Λ༻͍ͯదԠॲཧΛࢪ͢ߴ͍Ի੠σʔλΛ‫ͨ͠༻׆‬࿩ऀม‫ॲ׵‬ཧΛࢪ͢ख๏͕޿͘‫ݚ‬͜ͱͰɼ࿩ऀੑΛ‫͘ڧ‬൓өͨ͠ӳ‫ޠ‬Ի੠߹੒༻ HMM Λߏங͢‫͞ڀ‬Ε͍ͯΔɽ౷‫ܭ‬త੠࣭ม‫ͮ͘جʹ׵‬ख๏ͷྫͱͯ͠ɼӳΔɽͦͷࡍʹɼదԠ͢Δ HMM ύϥϝʔλΛ‫ݶ‬ఆ͠ɼӳ‫ޠ‬฼‫ޠ‬‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀґଘ HMM ͷग़ྗԻ੠ύϥϝʔλʹରͯ͠ɼ࿩ऀΒ͍͠ӆ཯ΛҰ෦߹੒Ի੠ʹ൓өͤ͞Δ͜ͱͰɼ೔ຊਓӳ‫ࢣڭ‬ແ͠࿩ऀదԠॲཧ͕Մೳͳࠞ߹ਖ਼‫ن‬෼෍Ϟσϧ ʢGMM:‫ޠ‬ͷ࿩ऀੑΛอ࣋ͭͭ͠ɼӆ཯ͷෆࣗવੑΛ௿‫͢ݮ‬Δɽ࣮‫ݧ‬తGaussian Mixture Modelʣ ʹ‫ͮ͘ج‬Ұରଟ࿩ऀม‫׵‬๏ [5] ΛධՁ݁Ռ͔Βɼ೔ຊਓӳ‫ޠ‬Ի੠߹੒ʹ͓͍ͯɼఏҊ๏ʹΑΓɼద༻͢Δख๏ [6] ͕͋Δɽ·ͨɼ࿩ऀదԠʹ‫ͮ͘ج‬ख๏ͷྫͱ͠೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀੑΛอ࣋ͭͭࣗ͠વੑΛվળͰ͖Δ͜ͱͯɼόΠϦϯΨϧ࿩ऀʹΑΔ֤‫ޠݴ‬ͷԻ‫ڹ‬ϞσϧؒͰঢ়ଶͷରΛࣔ͢ɽԠ෇͚Λߦ͍ɼผ‫Ͱޠݴ‬ਪఆ͞Εͨ࿩ऀదԠύϥϝʔλΛӳ‫ޠ‬Ի‫ڹ‬Ϟσϧʹద༻͢Δख๏ [7] ͕͋Δɽۙ೥Ͱ͸ɼૉยબ୒ॲ

2. HMM Ի੠߹੒ʹ͓͚ΔదԠٕज़ཧΛ༻͍ͯผ‫ޠݴ‬ͷԻ੠೾‫ܗ‬ΛϑϨʔϜ୯ҐͰӳ‫ޠ‬Ի੠ʹϚο

ਤ 1 ʹ HMM Ի੠߹੒ʹ͓͚ΔϞσϧదԠͷ֓ཁਤΛࣔ͢ɽϐϯά͠ɼಘΒΕͨӳ‫ޠ‬Ի੠͔Β HMM Λֶश͢Δख๏ [8] ΋

2. 1 HMM Ի੠߹੒ఏҊ͞Ε͍ͯΔɽ͜ΕΒͷख๏Ͱ߹੒͞ΕΔӳ‫ޠ‬Ի੠͸ɼൺֱ

HMM Ի੠߹੒Ͱ͸ɼԻ੠ͷεϖΫτϧύϥϝʔλɼԻ‫ݯ‬ύతࣗવੑ͸ߴ͍΋ͷͷɼ࿩ऀੑ͸ಉ‫͚͓ʹؒޠݴ‬Δ߹੒Ի੠ͱϥϝʔλɼঢ়ଶ‫ܧ‬ଓ௕ΛɼHMM ʹ‫ͮ͘ج‬౷Ұతͳ࿮૊ΈͰϞൺֱͯ͠ྼԽ͢Δ܏޲͕͋Δ [6]ɽσϧԽ͢Δɽ͜͜ͰɼԻ੠ಛ௃ྔ͸ΞΫηϯτ‫ܕ‬΍લ‫ޙ‬ͷԻૉ͜Εʹରͯ͠ɼͰ͖Δ‫ݶ‬Γ࿩ऀੑΛ‫͘ڧ‬൓өͤͨ͞ӳ‫ޠ‬Ի੠ͷӨ‫ڹ‬Λड͚ͯมಈ͢ΔͨΊɼ͜ΕΒͷมಈཁҼΛߟྀͨ͠ίΛ߹੒͢Δख๏ͱͯ͠ɼ೔ຊਓӳ‫ޠ‬ʢERJ: English Read byϯςΩετґଘԻૉϞσϧΛར༻͢ΔɽίϯςΩετ਺͸๲େJapaneseʣ [9] Λར༻͢Δ߹੒๏͕༗ޮͰ͋Δͱߟ͑ΒΕΔɽͰ͋ΔͨΊɼ֤ίϯςΩετʹର͢Δ࣭໰Ͱߏ੒͞ΕΔܾఆ໦ERJ Λ༻͍ͨख๏ͷྫͱͯ͠ɼӳ‫ޠ‬฼‫ޠ‬࿩ऀͱ೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀʹΑΔΫϥελϦϯάΛߦ͍ɼಉҰΫϥεʹଐ͢ΔϞσϧؒͰͷӳ‫ޠ‬Ի੠ؒͰ GMM Λֶश͠ɼ೔ຊ‫ޠ‬࿩ऀͷ੠࣭ʹม‫͞׵‬ΕϞσϧύϥϝʔλΛ‫ڞ‬༗͢Δ [14]ɽΫϥελϦϯά͸֤ HMMͨӳ‫ޠ‬฼‫ޠ‬࿩ऀԻ੠Λ HMM ͷֶशʹར༻͢Δख๏ [10] ͕‫ڍ‬ঢ়ଶ͓Αͼ֤Ի੠ύϥϝʔλʹରͯ͠ผʑʹߦΘΕΔɽΫϥε͛ΒΕΔɽ͔͠͠ͳ͕Βɼ೔ӳؒͷ‫ߏޠݴ‬଄ͷҧ͍ʹΑΓɼ೔c ͷग़ྗ֬཰෼෍ bc (ot ) ͸ɼ࣍ࣜͰද͞ΕΔɽຊਓӳ‫ޠ‬͸ӳ‫ޠ‬฼‫ޠ‬࿩ऀʹΑΔӳ‫ͱޠ‬େ͖͘ҟͳΔԻ‫ڹ‬తಛ௃Λ࣋ͭɽྫ͑͹ɼ੠ͷ‫ڧ‬ऑ΍௕୹ɼߴ௿ɼϦζϜ΍Πϯτωʔbc (ot ) = N (ot ; μc , Σc )γϣϯʹରԠ͢Δӆ཯ಛ௃ʹண໨͢Δͱɼ೔ຊ‫Ͱޠ‬͸Ϟʔϥഥͨͩ͠ɼot = ct , Δc
t , ΔΔctϦζϜʹର͠ɼӳ‫ޠ‬͸‫ڧ‬੎ഥϦζϜͰӆ཯͕มԽ͢Δ [11]ɽ·௃ྔ ct ͱͦͷҰ࣍ͱೋ࣍ͷಈతಛ௃ྔ Δct ɼΔΔct ͷ݁߹ϕͨɼ೔ຊਓӳ‫Ͱޠ‬͸ɼ฼Իͷૠೖɼஔ‫׵‬ɼ୤མͳͲͷൃԻ‫ޡ‬ΓΫτϧΛද͠ɼN (·; μc , Σc ) ͸ɼฏ‫ ۉ‬μc ɼ‫ڞ‬෼ࢄߦྻ Σc Λ͕සൟʹੜ͡Δ [12]ɽจ๏తʹਖ਼͍͠ൃ࿩಺༰Ͱ͋ͬͨͱͯ࣋ͭ͠ਖ਼‫ن‬෼෍Λද͢ɽ·ͨɼΫϥε c ͷঢ়ଶ‫ܧ‬ଓ௕෼෍ pc (dc )΋ɼӳ‫ޠ‬ಠࣗͷൃԻ΍཈༲Λ࠶‫͍ͳ͍͖ͯͰݱ‬೔ຊਓӳ‫Ͱޠ‬͸ɼ͸ɼ࣍ࣜͰද͞ΕΔɽӳ‫ޠ‬฼‫ޠ‬࿩ऀʹ͸൒෼ఔ౓͔͠௨͡ͳ͍ͱ͍͏ใࠂ΋͋Δ [13]ɽ͜ͷΑ͏ͳಛ௃Λ࣋ͭ೔ຊਓӳ‫ޠ‬Λ௚઀ϞσϧԽ͢Δ࿮૊ΈΛ༻͍ͨ৔߹ɼ࿩ऀੑ͸อ࣋͞ΕΔҰํͰɼಘΒΕΔ߹੒Ի੠ͷࣗવੑ͸ஶ͘͠ྼԽ͢ΔɽຊใࠂͰ͸ɼίϛϡχέʔγϣϯͷԁ‫׈‬Խ΍‫ڭޠݴ‬ҭࢧԉΛ 

pc (d) = N dc ; μc , σ 2c(1) ͸ɼ࣌ࠁ t ʹ͓͚Δ੩తಛ

(2)

͜͜Ͱɼd ͸ঢ়ଶ‫ܧ‬ଓ௕Λද͢ɽ߹੒࣌ʹ͸ɼೖྗςΩετͷίϯςΩετʹରԠ͢ΔΫϥεΛ HMM ঢ়ଶ͓ΑͼԻ੠ύϥϝʔλຖʹܾఆ͠ɼจ HMM Λ‫ܗ‬

—2—੒͢ΔͨΊͷग़ྗ֬཰෼෍͓Αͼঢ়ଶ‫ܧ‬ଓ௕෼෍͕ܾఆ͞ΕΔɽঢ়ଶ‫ܧ‬ଓ௕෼෍ͷ໬౓࠷େԽʹ‫͖ͮج‬ɼHMM ঢ়ଶ‫ྻܥ‬Λܾఆͨ͠‫ʹޙ‬ɼ੩తɾಈతಛ௃ྔؒͷ໌ࣔతͳ੍໿৚݅ԼͰ HMM໬౓Λ࠷େԽ͢ΔΑ͏ͳԻ੠ύϥϝʔλ‫ྻܥ‬Λੜ੒͢Δ [15]ɽ
ੜ੒͞ΕͨԻ੠ύϥϝʔλ‫͔ྻܥ‬ΒɼϘίʔμΛ༻͍ͯɼԻ੠೾‫ܗ‬Λ߹੒͢Δɽ

2. 2 HMM ʹ‫ͮ͘ج‬ϞσϧదԠ
HMM Ի੠߹੒Ͱ͸ɼϞσϧదԠٕज़Λ༻͍Δ͜ͱͰɼ͋Δ࿩ऀͷ HMM ͔Β໨ඪ࿩ऀͷ HMM ΛߏஙͰ͖Δɽ༧Ίֶश͓͍ͯͨ͠దԠ‫ݩ‬Ϟσϧͱ໨ඪ࿩ऀͷదԠσʔλΛ༻͍ͯɼదԠ‫ݩ‬ϞσϧͷύϥϝʔλΛม‫͢ܗ‬Δ͜ͱͰɼ໨ඪ࿩ऀ΁ͱదԠ͞ΕͨϞσϧ͕ಘΒΕΔɽຊߘͰ͸ɼదԠ‫͋Ͱݩ‬Δӳ‫ޠ‬฼‫ޠ‬࿩ऀͷ

HMM ʹରͯ͠ɼCSMAPLR ʢConstrained Structural Maximum a Posteriori Linear Regressionʣ ͱ MAP ʢMaximuma Posterioriʣ ਪఆΛ૊Έ߹Θͤͨ CSMAPLR ʴ MAP [16]Λ༻͍ͯɼϞσϧదԠॲཧΛࢪ͢ɽదԠ‫ݩ‬Ϟσϧͷ i ൪໨ͷ෼෍ʢঢ়ଶग़ྗ෼෍΍‫ܧ‬ଓ௕෼෍ʣʹ͓͚Δฏ‫ۉ‬ϕΫτϧΛ μi ɼ‫ڞ‬෼ࢄߦྻΛ Σi ͱͨ͠ͱ͖ɼCSMAPLR దԠ‫ޙ‬ͷฏ‫ۉ‬ϕΫτϧ μ̂i ͱ‫ڞ‬෼ࢄߦྻ Σ̂i ͸࣍ࣜͰ‫͞ࢉܭ‬ΕΔɽμ̂i = Aμi + bΣ̂i = AΣi AT(3)(4)ਤ2͜͜ͰɼదԠߦྻ A ͱόΠΞεϕΫτϧ b ͸ճ‫ؼ‬ύϥϝʔλͰ͋Γɼෳ਺ͷ෼෍͕ଐ͢Δճ‫ؼ‬Ϋϥε͝ͱʹਪఆ͞ΕΔɽӳ‫ޠ‬฼‫ޠ‬࿩ऀͷӳ‫ޠ‬Ի੠Λ༻͍ͨӆ཯ิਖ਼ॲཧͷྲྀΕ

Fig. 2 Flow of the prosody correction processing using English
speaker’s speech.

CSMAPLR Ͱ͸ɼճ‫ؼ‬ΫϥεΛ໦ߏ଄Ͱද‫͠ݱ‬ɼ਌ϊʔυʹ͓͚Δਪఆ݁ՌΛࢠϊʔυʹ͓͚Δࣄલ෼෍ͱͯ͠఻ൖͤ͞ಘΒΕΔ߹੒Ի੠͸೔ຊਓӳ‫ޠ‬Ի੠ͱಉ༷ɼෆࣗવͳԻ੠ͱͳͳ͕ΒɼదԠσʔλ͕༩͑ΒΕͨࡍͷճ‫ؼ‬ύϥϝʔλͷ MAPΔɽຊใࠂͰ͸ɼ೔ຊਓӳ‫ޠ‬Ի੠ͷࣗવੑΛେ͖͘ྼԽͤ͞ΔਪఆΛߦ͏ɽͳ͓ɼ໦ߏ଄ͱͯ͠ɼదԠ‫͋Ͱݩ‬Δӳ‫ޠ‬฼‫ޠ‬࿩ऀཁҼͱͯ͠ɼ‫ܧ‬ଓ௕͓Αͼύϫʔʹண໨͠ɼ͜ΕΒͷԻ੠ύϥͷ HMM ʹ͓͚ΔίϯςΩετΫϥελϦϯάͷܾఆ໦Λ༻͍ϝʔλʹରͯ͠͸ӳ‫ޠ‬฼‫ޠ‬࿩ऀ HMM ͷಛ௃Λ‫͢༻׆‬Δ͜ͱΔɽCSMAPLR ͰదԠ͞ΕͨϞσϧύϥϝʔλΛࣄલ෼෍ͷͰɼ೔ຊਓӳ‫ޠ‬ͷӆ཯Λิਖ਼͢Δख๏ΛఏҊ͢ΔɽϋΠύʔύϥϝʔλͱͯ͠ར༻͢Δ͜ͱͰɼ͞Βʹ MAP ਪఆΛࢪ͢ɽλ̂ = argmax P (o|λ) P (λ)λਤ 2 ʹఏҊ๏ͷखॱΛࣔ͢ɽ·ͣɼӳ‫ޠ‬฼‫ޠ‬࿩ऀͷӳ‫ޠ‬Ի੠Λ༻͍ͯɼӳ‫ޠ‬฼‫ޠ‬࿩ऀʹର͢Δ࿩ऀґଘ HMM Λֶश͢Δɽ(5)͜͜Ͱɼo ͸దԠσʔλɼP (o|λ) ͸ HMM ͷ໬౓ؔ਺ɼP (λ)͸‫ڞ‬໾ࣄલ෼෍Λද͠ɼλ̂ ͸ MAP ਪఆ͞ΕͨϞσϧύϥϝʔληοτΛද͢ɽͳ͓ɼHMM Ի੠߹੒Ͱ͸ɼεϖΫτϧύϥϝʔλɼԻ‫ݯ‬ύϥϝʔλɼঢ়ଶ‫ܧ‬ଓ௕͕ਖ਼‫ن‬෼෍ͰϞσϧԽ͞Ε͓ͯΓɼͦΕΒશͯʹରͯ͠దԠॲཧ͕ߦΘΕΔɽ͜ΕʹΑΓɼ෼અతಛ௃ͷΈͰͳ͘ӆ཯తಛ௃΋ಉ࣌ʹదԠՄೳʹͳΔɽ‫؍‬ଌσʔλͱͯ͠༻͍ΔԻ੠ύϥϝʔλ͸ɼର਺ύϫʔɼεϖΫτϧแབྷύϥϝʔλɼԻ‫ݯ‬ύϥϝʔλͰ͋Γɼ֤ύϥϝʔλʹର͢Δग़ྗ֬཰෼෍ͱঢ়ଶ‫ܧ‬ଓ௕෼෍͕ಘΒΕΔɽ࣍ʹɼ໨ඪ೔ຊਓ࿩ऀͷ೔ຊਓӳ‫ޠ‬Ի੠ΛదԠσʔλͱͯ͠ɼHMM ͷదԠॲཧΛߦ͏ɽ೔ຊਓӳ‫ޠ‬ͷԻ੠ύϥϝʔλͱͯ͠ɼӳ‫ޠ‬฼‫ޠ‬࿩ऀͷӳ‫ޠ‬Ի੠ͷ෼ੳ࣌ͱಉ༷ͷύϥϝʔλΛར༻͢ΔɽదԠ࣌ʹ͸ɼεϖΫτϧแབྷύϥϝʔλͱԻ‫ݯ‬ύϥϝʔλʹର͢ΔϞσϧύϥϝʔλʹ͸௨ৗͷదԠॲཧΛࢪ͕͢ɼର਺ύϫʔͱঢ়ଶ‫ܧ‬ଓ௕ʹର͢ΔϞσϧύϥϝʔλʹ͸దԠॲཧΛࢪͣ͞ɼӳ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀґଘ HMM ͷύϥϝʔλΛͦͷ··อ࣋͢3. ӆ཯ิਖ਼Λߟྀͨ͠೔ຊਓӳ‫ޠ‬Ի੠ʹର͢ΔదԠ๏໨ඪͱ͢Δ೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀੑΛ‫͘ڧ‬൓өͨ͠ӳ‫ޠ‬Ի੠߹੒༻ HMM Λߏங͢ΔͨΊʹɼ໨ඪ࿩ऀͷ೔ຊਓӳ‫ޠ‬Ի੠Λ༻͍ͯɼӳ‫ޠ‬฼‫ޠ‬࿩ऀͷ HMM ΛదԠ͢Δɽ͔͠͠ͳ͕Βɼ௨ৗͷదԠॲཧͷΑ͏ʹɼશ HMM ύϥϝʔλΛదԠ͢Δͱɼ೔ຊਓӳ‫ޠ‬Ի੠ͷಛ௃ΛશͯϞσϧԽͨ͠ HMM ͱͳΔͨΊɼΔɽຊదԠॲཧʹΑΓɼӳ‫ޠ‬฼‫ޠ‬࿩ऀͷύϫʔͱ‫ܧ‬ଓ௕͕൓ө͞Εͨ೔ຊਓӳ‫ ޠ‬HMM ͕ߏங͞ΕΔɽεϖΫτϧแབྷ͓ΑͼԻ‫ͯؔ͠ʹݯ‬͸ɼ໨ඪ೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀੑ͕৭ೱ͘൓ө͞ΕΔҰํͰɼࣗવੑʹେ͖ͳӨ‫ڹ‬Λ༩͑Δύϫʔͱ‫ܧ‬ଓ௕͸ӳ‫ޠ‬฼‫ޠ‬࿩ऀͷಛ௃͕൓ө͞ΕΔͨΊɼຊ HMM Λ༻͍Δ͜ͱͰɼ໨ඪ೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀੑΛग़དྷΔ‫ݶ‬Γอ࣋ͨ͠··ɼࣗવੑ͕վળ͞Εͨ೔ຊਓӳ‫ޠ‬Ի੠Λ߹੒Ͱ͖Δͱ‫ظ‬଴͞ΕΔɽ

—3—ਤ 3 ֤ϞσϧʹΑΔӳ‫߹ޠ‬੒Ի੠ͷύϫʔ‫੻ي‬ͷྫ ʢMonolingualʣɽൃ࿩಺༰͸ “I can seethat knife now.”Fig. 3 Example of power trajectories of English speech samples synthesized by individualmodels for a sentence “I can see that knife now.” ʢMonolingualʣ.

ఏҊ๏Ͱ͸ɼύϫʔ͓Αͼ‫ܧ‬ଓ௕ʹؔͯ͠͸ɼଞͷԻ੠ύϥଶ left-to-right ‫ܕ‬ͷӅΕηϛϚϧίϑϞσϧʢHSMM: Hiddenϝʔλͱൺֱͯ͠ɼ࿩ऀੑʹ༩͑ΔӨ‫ڹ‬͸গͳ͍͕ɼࣗવੑʹSemi-Markov Modelʣ [20] ͷֶशΛߦ͏ɽର਺ύϫʔͱϝϧέରͯ͠͸ແࢹͰ͖ͳ͍Ө‫ڹ‬Λ༩͑ΔͱԾఆ͍ͯ͠Δɽ͜ͷԾϓετϥϜ܎਺͸ಉҰετϦʔϜͰϞσϧԽ͢ΔɽCSMAPLRఆʹ͍ͭͯ͸ɼ࣍અͷ࣮‫ݧ‬తධՁʹ͓͍ͯ‫͢ূݕ‬Δɽ·ͨɼैదԠ࣌ʹ༻͍Δճ‫ྻߦؼ‬͸ɼ੩తಛ௃ྔɼ1 ࣍ͷಈతಛ௃ྔɼདྷ๏Ͱ͋Δ [6]ʙ[8] ͳͲͰ͸ɼҟ‫Ͱؒޠݴ‬࿩ऀม‫׵‬Λߦ͏ͨΊɼ͓Αͼɼ2 ࣍ͷಈతಛ௃ྔʹରԠͨ͠ϒϩοΫର֯ߦྻͱ͢Δɽύϫʔͱ‫ܧ‬ଓ௕ͷΈͰͳ͘ F0 ύλʔϯʹؔͯ͠΋ӳ‫ޠ‬฼‫ޠ‬࿩ͳ͓ɼ༧උ࣮‫ݧ‬ͷ݁Ռɼӳ‫ޠ‬฼‫ޠ‬࿩ऀґଘ HSMM Λ໨ඪ೔ຊऀͷಛ௃Λ༻͍Δ͜ͱʹͳΔ͕ɼఏҊ๏Ͱ͸ɼF0 ύλʔϯʹ‫ޠ‬࿩ऀʹదԠͨ͠ࡍʹɼ߹੒Ի੠ͷঢ়ଶ‫ܧ‬ଓ௕͕ஶ͘͠ෆࣗવؔͯ͠͸೔ຊਓӳ‫ޠ‬ͷಛ௃͕ͦͷ··൓ө͞ΕΔͨΊɼ໨ඪ೔ʹͳΔͱ͍͏܏޲͕‫ݟ‬ΒΕͨɽͦ͜Ͱɼӳ‫ޠ‬฼‫ޠ‬࿩ऀͷ HMMຊ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀੑΛΑΓ‫͘ڧ‬൓өͨ͠߹੒Ի੠͕ಘΒΕΔ

Λֶश͢Δࡍͷঢ়ଶ‫ܧ‬ଓ௕ʹର͢ΔίϯςΩετΫϥελϦϯͱߟ͑ΒΕΔɽ

άʹ͓͍ͯɼϧʔτ෦෼Ͱ౰֘Իૉ͕ϙʔζ͔൱͔Ͱେ͖͘ೋ

4. ࣮‫ݧ‬తධՁ෼ͨ͠‫Ͱޙ‬ɼଞͷ࣭໰ʹΑΔ௨ৗͷΫϥελϦϯάΛߦ͏ɽຊॲཧͰಘΒΕΔίϯςΩετΫϥελϦϯάͷܾఆ໦ʹ‫͖ͮج‬ɼ

4. 1 ࣮ ‫ ݧ‬৚ ݅ճ‫ؼ‬ύϥϝʔλΛਪఆ͢Δ͜ͱͰɼ্‫ه‬ͷ໰୊͕େ͖͘؇࿨͞

ֶशσʔλͱͯ͠ɼCMU ARCTIC Ի੠σʔλϕʔε [17] தΕΔ͜ͱΛ֬ೝࡁΈͰ͋Δɽͷஉੑӳ‫ޠ‬฼‫ޠ‬࿩ऀ 1 ໊ʹΑΔ A ηοτ 593 จΛ༻͍ΔɽධఏҊ๏ʹΑΔӆ཯ิਖ਼ͷޮՌΛධՁ͢ΔͨΊʹɼҎԼʹࣔ͢Ձσʔλ͸ಉ B ηοτ 50 จͱ͢ΔɽҰํͰɼ໨ඪ࿩ऀ͸ɼ20߹੒Ի੠Λ༻͍ͯɼ࿩ऀੑ‫ࣗͼٴ‬વੑʹؔ͢Δओ‫؍‬ධՁΛ࣮ࢪ୅உੑͷ೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀ 2 ໊ͱ͢Δɽ಺Ұਓ͸ɼཹֶ‫ݧܦ‬ͷແ͢Δɽ͍େֶӃੜͰ͋Γɼ೔ຊͷඪ४తͳӳ‫ڭޠ‬ҭΛड͚͖ͯͨ࿩ऀ••Ͱ͋ΓɼҎԼͰ͸ “Monolingual”ͱ͢Δɽ΋͏Ұਓ͸ɼ1 ೥ؒΦʔετϥϦΞ΁ͷཹֶ‫ݧܦ‬ͷ͋ΔେֶੜͰ͋ΓɼΑΓӳ‫ޠ‬ͷशख़౓͕ߴ͍࿩ऀͰ͋ΓɼҎԼͰ͸ “Bilingual”ͱ͢Δɽ্‫ه‬ೋ໊ͷ೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀ͕ൃ੠ͨ͠ ARCTIC Ի੠σʔλϕʔεதͷ A ηοτ 593 จΛదԠσʔλͱͯ͠࢖༻͢Δɽֶशσʔ
λɼධՁσʔλɼ͓ΑͼɼదԠσʔλͷαϯϓϦϯάप೾਺͸

16 kHz Ͱ͋ΔɽԻ੠ύϥϝʔλͷ෼ੳʹ͸ STRAIGHT ෼ੳ [18] Λ࢖༻͠ɼ

Nativeɿ ӳ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀґଘ HSMM ʹΑΔ߹੒Ի੠ERJɿ ೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀґଘ HSMMʢ593 จΛ༻ֶ͍ͯशʣʹΑΔ߹੒Ի੠• HMM+VCɿ ैདྷ๏ [6] ʢͨͩ͠ɼҰରଟ࿩ऀม‫Ͱ׵‬͸ͳ͘ERJ Λ༻͍ͨҰରҰ࿩ऀม‫׵‬Λ࢖༻ʣ ʹ‫͖ͮج‬ɼӳ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀґଘ HSMM ͷग़ྗԻ੠ύϥϝʔλʹରͯ͠ɼGMM ʹ‫ͮ͘ج‬౷‫ܭ‬త੠࣭ม‫׵‬ΛదԠͯ͠ಘΒΕΔ߹੒Ի੠• Adaptɿ શϞσϧύϥϝʔλΛదԠͤͨ͞దԠ HSMM ʹΑΔ߹੒Ի੠• Dur.ɿ ఏҊ๏ͱͯ͠ঢ়ଶ‫ܧ‬ଓ௕Ҏ֎ΛదԠͤͨ͞దԠ HSMMεϖΫτϧಛ௃ྔͱͯ͠ɼର਺ύϫʔ͓Αͼ 1 ͔࣍Β 24 ࣍ͷʹΑΔ߹੒Ի੠
• Dur.+Pow.ɿ ఏҊ๏ͱͯ͠ର਺ύϫʔͱঢ়ଶ‫ܧ‬ଓ௕Ҏ֎ΛదϝϧέϓετϥϜ܎਺Λ༻͍ΔɽԻ‫ݯ‬ಛ௃ྔͱͯ͠ɼର਺ F0Ԡͤͨ͞దԠ HSMM ʹΑΔ߹੒Ի੠͓Αͼ 5 प೾਺ଳҬʹ͓͚Δฏ‫ۉ‬ඇप‫ظ‬੒෼ [19] Λ࢖༻͢Δɽ࿩ऀੑͷධՁͰ͸ɼ೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀͷ೔ຊ‫ޠ‬෼ੳ߹੒Ի੠ΛϦϑϨʔϜγϑτ͸ 5 ms ͱ͢Δɽ͜ΕΒͷԻ੠ύϥϝʔλʹ 1ϑΝϨϯεͱͨ͠ 5 ஈ֊ DMOSʢDegradation Mean Opinion

࣍ͱ 2 ࣍ͷಈతಛ௃ྔΛՃ͑ͨ΋ͷΛ‫؍‬ଌϕΫτϧͱ͠ɼ5 ঢ়ScoreʣධՁΛ࣮ࢪ͢ΔɽࣗવੑͷධՁͰ͸ɼӳ‫ޠ‬Ի੠ͷࣗવ

—4—ϱϰϰϯ

DK^ϱDK^ϵϱйĐŽŶĨŝĚĞŶĐĞŝŶƚĞƌǀĂůϮϮϭϵϱйĐŽŶĨŝĚĞŶĐĞŝŶƚĞƌǀĂůϯZ:,DDнsĚĂƉƚƵƌ͘Ƶƌ͘нWŽǁ͘ϭZ:,DDнsĚĂƉƚƵƌ͘Ƶƌ͘нWŽǁ͘

ਤ 4 ࿩ऀੑʹؔ͢Δओ‫؍‬ධՁ݁Ռ (Monolingual)ਤ 6 ࿩ऀੑʹؔ͢Δओ‫؍‬ධՁ݁Ռ (Bilingual)Fig. 4 Result of opinion test on individuality (Monolingual).

Fig. 6 Result of opinion test on individuality (Bilingual).

ϱϱ

ϰ

ϰ

DK^

ϯ

DK^ϵϱйĐŽŶĨŝĚĞŶĐĞŝŶƚĞƌǀĂůϮϮϭϵϱйĐŽŶĨŝĚĞŶĐĞŝŶƚĞƌǀĂůϯEĂƚŝǀĞ

Z:,DDнsĚĂƉƚƵƌ͘Ƶƌ͘нWŽǁ͘ϭEĂƚŝǀĞ

Z:,DDнsĚĂƉƚƵƌ͘Ƶƌ͘нWŽǁ͘ਤ 5 ࣗવੑʹؔ͢Δओ‫؍‬ධՁ݁Ռ (Monolingual)ਤ 7 ࣗવੑʹؔ͢Δओ‫؍‬ධՁ݁Ռ ʢBilingualʣFig. 5 Result of opinion test on naturalness (Monolingual).

Fig. 7 Result of opinion test on naturalness ʢBilingualʣ.

ੑʹؔ͢Δ 5 ஈ֊ MOSʢMean Opinion ScoreʣධՁΛ࣮ࢪ͢ΛվળͰ͖Δ͜ͱ͕෼͔Δɽ“Monolingual”ͱ “Bilingual”ͷ

Δɽඃ‫ऀݧ‬͸ɼ೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀ 6 ໊Ͱ͋Δɽ྆࿩ऀʹ͓͍ͯվળ܏޲͕‫ݟ‬ΒΕΔ͕ɼ“Monolingual”ʹ͓͚

4. 2 ࣮ ‫ ݁ ݧ‬ՌΔվળ܏޲͕ஶ͍͜͠ͱ͕෼͔ΔɽҰํͰɼ‫ܧ‬ଓ௕͓Αͼύਤ 3 ʹɼ֤ख๏ʹΑΔύϫʔ‫੻ي‬ͷྫΛࣔ͢ɽ“Native”ͱൺϫʔΛิਖ਼ͨ͠ “Dur.+Pow.”ʹؔͯ͠͸ɼࣗવੑ͸ “Dur.”ͱ

ֱ͠ɼ“ERJ”͸Իૉ‫ܧ‬ଓ௕͕ҟͳ͓ͬͯΓɼύϫʔ‫͍ͭʹ੻ي‬ಉ౳͕ͩɼ࿩ऀੑ͕ “Monolingual”ʹ͓͍ͯ “ERJ”ΑΓ΋ྼͯ΋ࢠԻͷύϫʔ͕খ͍͞ͳͲҟͳΔಛ௃͕‫ݟ‬ΒΕΔɽ͜ΕʹԽ͢Δ܏޲͕‫ݟ‬ΒΕΔɽ͜ͷ‫ݪ‬ҼΛௐࠪ͢ΔͨΊʹɼਤ 8 ʹ

ର͠ɼ“Dur.”Ͱ͸Իૉ‫ܧ‬ଓ௕͕ิਖ਼͞Ε͍ͯΔ͜ͱ͕෼͔Δɽ

“Monolingual”͓Αͼ “Bilingual”ʹର͢Δ “Dur.+Pow.” ʹΑ·ͨɼ͜Εʹ൐͍ɼύϫʔ‫੻ي‬΋ “Native”ͷ΋ͷʹۙͮ͘܏޲Δ߹੒Ի੠ͱ “Native”ʹΑΔ߹੒Ի੠ͷεϖΫτϩάϥϜͷҰ͕‫ݟ‬ΒΕΔɽ͞Βʹɼ“Dur.+Pow.”ʹΑΓɼ“Native”ͱಉ౳ͷ෦Λࣔ͢ɽਤ͔Βɼಛʹແ੠ࢠԻ෦/s/ʹ͓͍ͯɼ“Bilingual”

ύϫʔ‫͕੻ي‬ಘΒΕΔ͜ͱ͕෼͔Δɽͱ “Native”Ͱ͸ൺֱత‫׈‬Β͔ͳεϖΫτϧભҠ͕֬ೝͰ͖Δਤ 4ɼ ਤ 5 ʹͦΕͧΕɼ“Monolingual”ʹ͓͚Δ࿩ऀੑͱࣗ

͕ɼ“Monolingual”ʹؔͯ͠͸ଟগͷෆ࿈ଓ෦෼͕֬ೝͰ͖Δɽવੑʹؔ͢ΔධՁ݁ՌΛɼਤ 6ɼ ਤ 7 ʹͦΕͧΕɼ“Bilingual”

߹੒Ի੠Λௌऔ͢Δͱɼ“Monolingual”ͷ৔߹͸ɼύϫʔิਖ਼ʹ͓͚Δ࿩ऀੑͱࣗવੑʹؔ͢Δओ‫؍‬ධՁ݁ՌΛࣔ͢ɽ·ͣɼʹΑΓɼ/s/ͷ෦෼ʹ͓͍ͯࡶԻ͕‫ڧ‬ௐ͞ΕͨΑ͏ͳԻ੠ͱͳ౷‫ܭ‬త੠࣭ม‫׵‬Λར༻ͨ͠ख๏ “HMM+VC”ʹண໨͢ΔͱɼΔɽ͜ΕΒͷ͜ͱ͔Βɼద੾ͳεϖΫτϧߏ଄͕ಘΒΕ͍ͯͳ

“Monolingual”ʹ͓͍ͯɼ“ERJ”ͱൺֱͯ͠ɼ࿩ऀੑ͕େ͖͘

͍Իૉʹରͯ͠ύϫʔิਖ਼Λࢪ͢ͱɼѱӨ‫͕ڹ‬ੜ͡Δ͜ͱ͕෼ྼԽ͢Δ܏޲͕‫ݟ‬ΒΕΔɽ·ͨɼࣗવੑʹؔͯ͠΋ए‫ྼׯ‬Խ͢

͔Δɽ

Δ܏޲͕‫ݟ‬ΒΕΔɽ“Bilingual”ʹ͓͍ͯ΋ɼྼԽͷఔ౓͸খҎ্ͷ݁Ռ͔ΒɼఏҊ๏ʹΑΔ‫ܧ‬ଓ௕ิਖ਼ʹΑΓɼ೔ຊਓӳ͘͞ͳΔ΋ͷͷɼ࿩ऀੑʹؔͯ͠ಉ༷ͷ܏޲͕‫ݟ‬ΒΕΔɽ͜Ε‫ޠ‬ͷ࿩ऀੑΛอ࣋ͭͭ͠ɼࣗવੑͷߴ͍ӳ‫ޠ‬Ի੠Λ߹੒Ͱ͖ΔΒ͸ɼ੠࣭ม‫ॲ׵‬ཧʹΑΔ඼࣭ྼԽʹΑΔ΋ͷͱߟ͑ΒΕΔɽ

͜ͱ͕෼͔Δɽຊิਖ਼ॲཧ͸ɼӳ‫ޠ‬शख़౓͕௿͍࿩ऀʹରͯ࣍͠ʹɼશϞσϧύϥϝʔλΛదԠͨ͠ख๏ “Adapt”ʹண໨͢େ͖ͳࣗવੑվળޮՌΛ΋ͨΒ͢΋ͷͰ͋Γɼӳ‫ޠ‬शख़౓͕ߴ

Δͱɼ֓Ͷ “ERJ”ͱಉ౳ͷࣗવੑ͓Αͼ࿩ऀੑ͕ಘΒΕΔ͍͜࿩ऀʹରͯ͠΋༗ޮͰ͋Δ͜ͱ͕෼͔ΔɽҰํͰɼύϫʔิͱ͕෼͔Δɽ͜Εʹରͯ͠ɼఏҊ๏ʹΑΔ‫ܧ‬ଓ௕ิਖ਼ “Dur.”ਖ਼ʹؔͯ͠͸ɼӳ‫ޠ‬शख़౓͕௿͍࿩ऀʹରͯ͠͸ɼύϫʔͱεΛߦ͏͜ͱͰɼ“ERJ”ͱಉ౳ͷ࿩ऀੑΛอ࣋ͭͭ͠ɼࣗવੑ

ϖΫτϧߏ଄ͱͷෆҰகʹΑΓɼѱӨ‫͕ڹ‬ੜ͡ಘΔ͜ͱ͕෼͔

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024680246802468ਤ8֤छ߹੒Ի੠ͷεϖΫτϩάϥϜʢൃ࿩จதͷ “Philip’s.”ͱ͍
͏୯‫ʹޠ‬ରԠʣͷྫɽ্͔Βɼ“Dur.+Pow.ʢMonolingualʣ”ɼ

“Dur.+Pow.ʢBilingualʣ”ɼ“Native”Λද͢ɽFig. 8 Example of spectrograms of synthetic speech samples
for a word fragment “Philip’s.” From top to bottom:“Dur.+Pow.ʢMonolingualʣ”ɼ“Dur.+Pow.ʢBilingualʣ”and “Native.”ʣ

Δɽ͜ͷͨΊɼύϫʔͷิਖ਼ॲཧʹԠͯ͡ɼεϖΫτϧߏ଄΋
ิਖ਼͢Δඞཁ͕͋Δ͜ͱ͕෼͔Δɽ

5. · ͱ ΊຊใࠂͰ͸ɼ೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀੑΛอ࣋ͭͭ͠ɼΑΓࣗવͳӳ‫ޠ‬Ի੠Λ߹੒͢Δख๏ͱͯ͠ɼ೔ຊਓӳ‫ޠ‬Ի੠Λ༻͍ͨHMM Ի੠߹੒ϞσϧదԠʹ‫ͮ͘ج‬ӆ཯ิਖ਼๏ΛఏҊͨ͠ɽ࣮‫ݧ‬తධՁ݁Ռ͔Βɼ‫ܧ‬ଓ௕ͷิਖ਼ʹΑΓɼ೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀͷ࿩ऀੑΛอ࣋ͭͭ͠ɼࣗવੑΛվળͰ͖Δ͜ͱΛࣔͨ͠ɽҰํͰɼӳ‫ޠ‬शख़౓͕௿͍࿩ऀʹؔͯ͠͸ɼύϫʔิਖ਼͕ѱӨ‫ڹ‬Λ΋ͨΒ͢͜ͱ͕෼͔ͬͨɽࠓ‫ޙ‬͸ɼධՁऀͷ฼ࠃ‫ޠ‬ͷӨ‫[ ڹ‬21] ΍೔ຊ‫ޠ‬฼‫ޠ‬࿩ऀͷӳ‫ޠ‬शख़౓ͷӨ‫[ ڹ‬9] ʹ͍ͭͯௐࠪ͢Δͱͱ΋ʹɼεϖΫτϧߏ଄ͷิਖ਼ॲཧʹ͍ͭͯ΋‫ݕ‬౼ΛਐΊΔɽँࣙຊ‫ڀݚ‬ͷҰ෦͸ɼʢಠʣ৘ใ௨৴‫ߏػڀݚ‬ͷҕୗ‫ڀݚ‬ʮ஌ࣝɾ‫ޠݴ‬άϦουʹ‫ͮ͘ج‬ΞδΞҩྍަྲྀࢧԉγεςϜͷ‫ڀݚ‬։ൃʯ͓Αͼ JSPS Պ‫ݚ‬අ 26280060 ͷॿ੒Λड͚࣮ࢪͨ͠΋ͷͰ͋Δɽจ‫ݙ‬[1] K. Oura, K. Tokuda, J. Yamagishi, S. King, and M.
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