3-7-1

スペシャル・セッション〔ここまで来た声質変換技術 -実用可能性の視点からの現状認識と将来展望-〕౷‫ܭ‬తख๏ʹ‫ͮ͘ج‬ϦΞϧλΠϜ੠࣭ม‫ʹ׵‬ΑΔԻ੠ੜ੒‫ػ‬ೳ֦ு∗˓‫ాށ‬ஐ‫( ج‬ಸྑઌ୺େɾ৘ใ)1͸͡ΊʹԻ੠ίϛϡχέʔγϣϯͰ͸ɼॴ๬ͷ‫ޠݴ‬৘ใΛԻ੠৴߸΁ͱม‫͠׵‬ɼύϥ‫ޠݴ‬৘ใ͓Αͼඇ‫ޠݴ‬৘ใͱ߹Θͤͯɼಉ࣌ʹ૬खʹ఻ୡ͢Δ͜ͱ͕Ͱ͖ΔɽԻ੠৴߸ʹ͸ଟ͘ͷ৘ใ͕ຒΊࠐ·ΕΔ΋ͷͷɼͦͷੜ੒ʹ͔͔Δ࣌ؒ͸୹͘ɼଈ࣌ੑ͸‫ۃ‬Ίͯߴ͍ɽ·ͨɼԻ੠ੜ੒աఔʹ͓͚Δ෺ཧత੍໿͸ɼ‫ݸ‬ਓ͕ੜ੒Ͱ͖Δ੠৭ͷൣғΛ‫ݶ‬ఆ͠ɼԻ੠৴߸ʹ‫ݸ‬ਓੑΛ༩͑ΔҰͭͷཁҼͱͳΔɽҰํͰɼ͜ͷ੍໿ͷ‫ʹނ͞ڧ‬ɼ࣌ͱͯ͠ɼίϛϡχέʔγϣϯʹ͓͚Δোน͕༰қʹ΋ͨΒ͞ΕΔɽྫ͑͹ɼԻ‫ݯ‬ੜ੒‫׭ث‬΍ௐԻ‫͕׭ث‬ਖ਼ৗʹಈ࡞͠ͳ͘ͳΔͱɼਂࠁͳൃ੠ো֐Λ‫͍ױ‬ɼԻ੠ίϛϡχέʔγϣϯʹࢧোΛ͖ͨ͢ɽԾʹɼ෺ཧత੍໿Λ௒͑ͨԻ੠ੜ੒ΛՄೳͱ͢Δ‫ػ‬ೳ͕࣮‫͞ݱ‬ΕΕ͹ɼ͜ͷΑ͏ͳোนΛແ͘͢͜ͱ͕Ͱ͖Δɽ͞Βʹ͸ɼ֤‫ݸ‬ਓ͕ҙਤతʹ੍‫͖Ͱޚ‬Δ੠࣭ͷൣғ͕޿͕ΓɼΑΓଟ༷ͳՎএද‫ݱ‬΍ൃ੠ද‫ݱ‬΋ੜ·ΕΔͱ༧૝͞ΕΔɽ੠࣭ม‫׵‬͸ɼ‫ޠݴ‬৘ใΛอ࣋͠ͳ͕Βɼॴ๬ͷඇ‫ݴ‬‫ޠ‬৘ใ΍ύϥ‫ޠݴ‬৘ใΛม‫͢׵‬ΔԻ੠৘ใॲཧٕज़Ͱ͋Δɽ੠࣭ม‫׵‬Λ࣮‫͢ݱ‬Δ࿮૊Έ͸༷ʑͰ͋Δ͕ɼதͰ΋ɼೖྗ͞ΕͨԻ੠৴߸ʹରͯ͠ม‫ॲܗ‬ཧΛߦ͏࿮૊Έ͸ɼ‫͔͘ݹ‬Β‫͞ڀݚ‬Ε͍ͯΔɽ౷‫ܭ‬తख๏ʹΑΓม‫ॲܗ‬ཧΛ‫ٻ‬ΊΔ࿮૊Έ [1] ͕ओྲྀͰ͋Γɼ֬཰ϞσϧΛ༻͍ͨख๏ [2] ͕໨֮·͍͠ൃలΛ਱͍͛ͯΔɽۙ೥Ͱ͸ɼԻ੠৴߸ͷ࣌‫ྻܥ‬σʔλͱͯ͠ͷಛ௃Λ࠷େ‫͢༻׆ʹݶ‬Δม‫׵‬๏͕ఏҊ͞Ε [3]ɼ͞Βʹ͸ɼϦΞϧλΠϜม‫ॲ׵‬ཧ΁ͷ֦ு΋ͳ͞Ε͍ͯ
Δ [4]ɽԻ੠ίϛϡχέʔγϣϯʹ͓͍ͯຊ࣭తʹॏཁͳಛ௃Ͱ͋Δଈ࣌ੑΛຬͨ͢͜ͱ͕Ͱ͖ΔͨΊɼԻ੠ੜ੒‫ػ‬ೳ֦ுΛ࣮‫͢ݱ‬ΔՄೳੑΛେ͍ʹൿΊٕͨज़ͱ͍͑ΔɽຊߘͰ͸ɼ֤छ੠࣭ม‫ٕ׵‬ज़Λ֓આͨ͠‫Ͱޙ‬ɼ౷‫ܭ‬తख๏ʹ‫ͮ͘ج‬ϦΞϧλΠϜ੠࣭ม‫ٕ׵‬ज़ʹ͍ͭͯৄ͘͠ड़΂Δɽ·ͨɼϦΞϧλΠϜ੠࣭ม‫ʹ׵‬ΑΔԻ੠ੜ੒‫ػ‬ೳ֦ுͷԠ༻ྫʹ͍ͭͯ঺հ͠ɼࠓ‫ޙ‬ͷ՝୊Λड़΂Δɽ2੠࣭ม‫׵‬ͷ࿮૊Έ੠࣭ม‫׵‬ͷग़ྗ͸ɼॴ๬ͷඇ‫ޠݴ‬৘ใ΋͘͠͸ύϥ‫ޠݴ‬৘ใΛ࣋ͭԻ੠৴߸Ͱ͋ΔɽҰํͰɼೖྗͱͯ͠༻͍Δ৘ใʹ͍ͭͯ͸ɼ༷ʑͳ΋ͷ͕ߟ͑ΒΕΔɽҎԼͰ͸ɼେ͖͘ࡾͭͷ࿮૊Έʹ෼ྨ͢Δɽ

2.1Ի੠ೖྗೖྗ͞ΕͨԻ੠৴߸ʹରͯ͠ม‫ॲ׵‬ཧΛࢪ͢࿮૊ΈͰ͋Γɼ੠࣭ม‫׵‬͸ɼ͜ͷ࿮૊ΈΛࢦ͢༻‫ͯ͠ͱޠ‬༻͍ΒΕΔ͜ͱ΋ଟ͍ɽೖྗԻ੠ͱग़ྗԻ੠ͷಉҰ಺༰ൃ࿩ηοτΛֶशσʔλͱͯ͠༻͍ͯɼม‫਺ؔ׵‬Λ∗‫ٻ‬ΊΔ౷‫ܭ‬తख๏ [1] ͕ओྲྀͰ͋Γɼߴ౓ͳม‫ॲ׵‬ཧ͕࣮‫ݱ‬ՄೳͰ͋Δɽࠞ߹ਖ਼‫ن‬෼෍ϞσϧʢGaussian
mixture model: GMMʣ[2] ΍χϡʔϥϧωοτϫʔΫ [5] ΛॳΊͱͯ͠ɼۙ೥Ͱ͸ɼඇෛ஋ߦྻ෼ղʹ‫ج‬ͮ͘ख๏ [6] ΍ਂ͍ߏ଄Λ࣋ͭωοτϫʔΫʹ‫ͮ͘ج‬ख๏ [7] ͳͲɼ༷ʑͳม‫׵‬๏͕ఏҊ͞Ε͍ͯΔɽςΩετ৘ใΛೖྗͱͯ͠ඞཁͱ͠ͳ͍ͨΊɼϦΞϧλΠϜॲཧʹద͍ͯ͠Δͱ͍͏ͷ͕࠷େͷಛ௃Ͱ͋Δɽ·ͨɼ‫ޠݴ‬ґଘੑ͕௿͍ͱ͍͏ར఺΋͋Δɽͳ͓ɼϦΞϧλΠϜॲཧ͓ΑͼςΩετ৘ใ͕ະ஌ͱ͍͏৚݅ʹ͓͍ͯɼӆ཯తಛ௃ྔΛߴਫ਼౓ʹม‫׵‬͢Δͷ͸ࠔ೉Ͱ͋ΔͨΊɼ୹࣌ؒಛ௃ྔͰ͋Δ෼અతಛ௃ྔΛओͳม‫׵‬ର৅ͱ͢Δ‫͕ڀݚ‬ଟ͍ɽ2.2ςΩετೖྗςΩετΛೖྗͱͯ͠Ի੠Λग़ྗ͢ΔςΩετԻ
੠߹੒ʢText-to-Speech: TTSʣʹ͓͍ͯɼग़ྗԻ੠ͷ੠࣭ม‫׵‬Λߦ͏ॲཧ͸‫͔͘ݹ‬Β‫͞ڀݚ‬Ε͍ͯΔɽ౷‫ܭ‬తύϥϝτϦοΫԻ੠߹੒ [8] ͷ୅දతख๏Ͱ͋ΔӅΕϚϧίϑϞσϧʢhidden Markov model: HMMʣʹ‫ͮ͘ج‬Ի੠߹੒๏ [9] Ͱ͸ɼHMM ͷύϥϝʔλʹରͯ͠ม‫ॲܗ‬ཧΛࢪ͢͜ͱͰɼग़ྗԻ੠ͷ੠࣭Λม‫׵‬͢Δ͜ͱ͕Ͱ͖Δɽ࠷໬ઢ‫ܗ‬ճ‫[ ؼ‬10] ΍࠷େࣄ‫֬ޙ‬཰ਪఆ [11]ɼฏ‫ۉ‬੠ [12]ɼ‫ݻ‬༗੠ [13, 14]ɼॏճ‫ؼ‬Ϟσϧ [15] ͳͲɼଟछଟ༷ͳϞσϧదԠٕज़͕ద༻͞Ε͓ͯΓɼۙ೥ܶతͳൃలΛ਱͍͛ͯΔٕज़Ͱ͋ΔɽςΩετ৘ใΛೖྗͱ͢ΔͨΊɼ෼અతಛ௃ྔͷΈͰͳ͘ӆ཯తಛ௃ྔ΋ର৅ͱͨ͠੠࣭ม‫ॲ׵‬ཧΛ༰қʹ࣮‫͖Ͱݱ‬Δɽ·ͨɼԻ੠߹੒Ϟσϧ͸େྔͷσʔλΛ༻͍ͯࣄલʹֶश͞ΕΔͨΊɼ൚ԽॲཧʹΑΓɼԻ੠෼ੳ‫߹͕ࠩޡ‬੒Ի੠ʹ༩͑ΔӨ‫ڹ‬Λ௿‫͖Ͱݮ‬ΔɽҰํͰɼԻ੠ೖྗͱൺ΂Δͱଈ࣌ੑʹ๡͍͠ɽ

2.3Ի੠ɾςΩετೖྗԻ੠ͱςΩετͷ྆ํΛೖྗͱͯ͠ɼॴ๬ͷग़ྗԻ੠ΛಘΔ࿮૊Έ΋‫͞ڀݚ‬Ε͍ͯΔɽͦͷҰྫͱͯ͠ɼTTS Ͱग़ྗ͞ΕΔ߹੒Ի੠ʹର͢Δ‫ॲޙ‬ཧͱͯ͠ɼ੠࣭ม‫׵‬Λߦ͏࿮૊Έ͕‫͛ڍ‬ΒΕΔɽ೾‫઀ܗ‬ଓํࣜͳͲʹ‫ ͮ͘ج‬TTS ʹରͯ͠΋੠࣭ม‫׵‬Λ༰қʹద༻Ͱ͖ΔͳͲɼҠ২ੑ͸ߴ͍ɽ·ͨɼςΩετ৘ใΛ༻͍ͯม‫਺ؔ׵‬Λ‫ه‬ड़͢Δ͜ͱ͕Ͱ͖ΔͨΊɼӆ཯తಛ௃ྔͷม‫ʹ׵‬΋ରԠ͠΍͍͢ [16–18]ɽ
TTS ʹ͓͚Δ߹੒ॲཧͷ࣌఺ͰೖྗԻ੠Λ‫͢༻׆‬Δ͜ͱͰɼॴ๬ͷ߹੒Ի੠Λ࣮‫͢ݱ‬Δ࿮૊Έ΋͋Δɽྫ͑͹ɼՎ੠߹੒ʹ͓͚Δ VocaListener[19] ʹ୅ද͞ΕΔΑ͏ʹɼೖྗԻ੠ͷӆ཯తಛ௃Λ࣋ͭ߹੒Ի੠͕ಘΒΕΔΑ͏ʹ߹੒ॲཧΛ࠷దԽ͢Δ͜ͱͰɼ߹੒Ի੠ΛೖྗԻ੠Ͱௐ੔͢Δ‫ػ‬ೳΛ࣮‫͖Ͱݱ‬ΔɽHMMΛ༻͍ͨ੠࣭ม‫׵‬๏ [20] ΋ɼྨࣅͷ΋ͷͱΈͳͤΔɽ

Augmented speech production based on real-time statistical voice conversion. by TODA, Tomoki (NaraInstitute of Science and Technology)

日本音響学会講演論文集- 1457 -

2013年9月

3౷‫ܭ‬తख๏ʹ‫ͮ͘ج‬ϦΞϧλΠϜม‫׵‬੠࣭ม‫ʹ׵‬ΑΔԻ੠ੜ੒‫ػ‬ೳ֦ுͰ͸ɼϦΞϧλΠϜม‫ॲ׵‬ཧ͕ඞཁෆՄܽͱͳΔͨΊɼԻ੠ೖྗʹ‫ͮ͘ج‬੠࣭ม‫׵‬ͷ࿮૊Έ͕༗ޮͰ͋ΔɽҰྫͱͯ͠ɼ
GMM Λ༻͍ͨ‫ྻܥ‬୯Ґͷ੠࣭ม‫׵‬๏ [3] ʹ‫ͮ͘ج‬ϦΞϧλΠϜม‫ॲ׵‬ཧ [4] ʹ͍ͭͯड़΂Δɽ3.1ಛ௃ྔநग़ॲཧೖྗԻ੠ͷ֤ϑϨʔϜʹ͓͍ͯɼ؆қͳεϖΫτϧ෼ੳΛߦ͍ɼεϖΫτϧแབྷύϥϝʔλϕΫτϧ xt
Λநग़͢Δ1 ɽ͜͜Ͱɼt ͸ϑϨʔϜ൪߸Λද͢ɽϑϨʔϜ t ʹ͓͚ΔεϖΫτϧηάϝϯτಛ௃ྔͱͯ͠ɼ౰֘ϑϨʔϜ͓Αͼલ‫ ޙ‬C ϑϨʔϜͷεϖΫτ
ϧแབྷύϥϝʔλϕΫτϧΛ༻͍ͯɼD(x) ࣍‫ݩ‬ೖྗಛ௃ྔϕΫτϧ X t Λ࣍ࣜʹͯ‫͢ࢉܭ‬Δɽ
X t = A x+ b (1)t−C , · · · , xt , · · · , xt+C͜͜Ͱɼ ͸సஔΛࣔ͢ɽߦྻ A ͓ΑͼϕΫτϧ b͸ηάϝϯτಛ௃ྔநग़ͷͨΊͷύϥϝʔλΛࣔ͢2 ɽग़ྗಛ௃ྔͱͯ͠ɼ݁߹੩తɾಈతಛ௃ྔϕΫτϧ Y t = yΛ༻͍Δɽ͜͜Ͱɼy t ͸ϑϨʔϜt , Δy t(y)t ʹ͓͚Δ D ࣍‫ݩ‬ͷԻ੠ύϥϝʔλϕΫτϧͱ͠ɼಈతಛ௃ྔϕΫτϧ Δy t ͸࣍ࣜʹͯ‫͢ࢉܭ‬Δɽ

Δy t=y t − y t−1ֶशॲཧֶशσʔλͱͯ͠ɼೖྗԻ੠ͱग़ྗԻ੠ͷಉҰൃ࿩ରͰߏ੒͞ΕΔύϥϨϧσʔλΛ༻͍ΔɽύϥϨϧσʔλʹରͯ͠ɼϑϨʔϜؒͷରԠ෇͚Λߦ͏͜ͱͰ,YಘΒΕΔ݁߹ೖྗɾग़ྗಛ௃ྔϕΫτϧ X ttΛ༻͍ͯɼೖྗಛ௃ྔϕΫτϧͱग़ྗಛ௃ྔϕΫτϧͷ݁߹֬཰ີ౓ؔ਺Λɼ࣍ࣜʹࣔ͢ GMM ʹΑΓϞσϧԽ͢Δ [22]ɽ

P X t , Y t |λ(X,Y )

=M

m=1

αm N(X))
Σ(XX) Σ(XY
X t μmm; (Y ) , mX)Y)
Y t μmΣ(YΣ(Ymm(3)

͜͜ͰɼN (·; μ, Σ) ͸ฏ‫ۉ‬ϕΫτϧ μ ͓Αͼ‫ڞ‬෼ࢄߦྻ Σ ͷਖ਼‫ن‬෼෍Λࣔ͢ɽ·ͨɼm ͸෼෍൪߸ɼM ͸෼෍਺Λද͢ɽGMM ͷύϥϝʔληοτ͸ λ(X,Y )Ͱࣔ͞Εɼ‫ݸ‬ʑͷ෼෍ʹର͢Δ෼෍ॏΈ αm ɼೖྗ͓(X)(Y )Αͼग़ྗʹର͢Δฏ‫ۉ‬ϕΫτϧ μm ɼμm ͱ‫ڞ‬෼ࢄ)X)Y)ߦྻ Σ(XX)
ɼΣ(XYɼΣ(YɼΣ(YͰߏ੒͞ΕΔɽ
mmmm1 ྫ͑͹ɼ‫ݻ‬ఆ෼ੳ૭Λ༻͍ͨߴ଎ϑʔϦΤม‫ ͱ׵‬1 ࣍ͷશҬ௨աϑΟϧλϦϯάͰಘΒΕΔϝϧέϓετϥϜ܎਺Λ༻͍Δɽ
2 ྫ͑͹ɼ݁߹੩తɾಈతಛ௃ྔϕΫτϧΛநग़͢Δճ‫ྻߦؼ‬΍ɼओ੒෼෼ੳʹΑΓಘΒΕΔ‫ݻ‬༗ϕΫτϧ͓Αͼฏ‫ۉ‬ϕΫτϧΛ༻͍ͯઃఆ͢Δɽ

日本音響学会講演論文集ม‫ॲ׵‬ཧߴ͍ม‫׵‬ਫ਼౓ΛಘΔʹ͸ɼϑϨʔϜؒͷ૬ؔ΍ߴ࣍౷‫Ͳͳྔܭ‬ɼ࣌‫ྻܥ‬σʔλͱͯ͠ͷಛ௃Λɼద੾ʹϞσϧԽ͢Δ͜ͱ͕ॏཁͰ͋Δɽม‫׵‬ର৅ͱͳΔೖྗԻ੠͕ɼϑϨʔϜ਺ T ͷ࣌‫ྻܥ‬σʔλͰද͞ΕΔͱ͠ɼɼೖྗಛ௃ྔ‫ྻܥ‬ϕΫτϧΛ X = X 
1 , · · · , XTग़ྗಛ௃ྔ‫ྻܥ‬ϕΫτϧΛ Y = Y ͱ
1 ,··· ,Y T͢Δɽ࠷໬‫ྻܥ‬ม‫׵‬๏ [3] Ͱ͸ɼม‫׵‬੩తಛ௃ྔ‫ྻܥ‬ϕΫτϧ ŷ = ŷ ͸࣍ࣜͰ‫ٻ‬ΊΒΕΔɽ1 , · · · , ŷ T ωŷ = argmax P Y |X, λ(X,Y ) P v (y ) |λ(v)ysubject to Y = W y(4)(5)͜͜ͰɼW ͸੩తಛ௃ྔ‫ྻܥ‬ϕΫτϧΛ݁߹੩తɾಈతಛ௃ྔ‫ྻܥ‬ϕΫτϧ΁ͱ֦ு͢Δ 2D(y) T × D(y) Tͷߦྻ [23] Ͱ͋Δɽࣜ (3) ΑΓɼX ͕༩͑ΒΕͨࡍͷY ͷ৚݅෇͖֬཰ີ౓ؔ਺͸࣍ࣜͰϞσϧԽ͞ΕΔɽTP Y |X, λ(X,Y ) =P Y t |X t , λ(X,Y )
P Y t |X t , λ(X,Y )=(2)֤छԠ༻ྫʹԠͯ͡ɼεϖΫτϧแབྷύϥϝʔλ΍ඇप‫ظ‬੒෼ύϥϝʔλɼ‫ج‬ຊप೾਺ύϥϝʔλͳͲΛɼԻ੠ύϥϝʔλͱͯ͠༻͍Δɽͳ͓ɼग़ྗԻ੠ʹର͢Δύϥϝʔλநग़ʹ͸ɼSTRAIGHT[21] ͳͲͷߴਫ਼౓ͳԻ੠෼ੳ‫ܥ‬Λ༻͍Δ͜ͱ͕ॏཁͰ͋Δɽ

3.2

3.3

M


(Y |X)

αm,t(6)t=1

(Y |X)|X)
N Y t ; μm,t , Σ(Ym(7)m=1͜͜Ͱɼࣜ (7) ΋ GMM Ͱද͞Εɼͦͷύϥϝʔλ͸
(Y |X)(8)
αm,t = P m|X t , λ(X,Y )−1(Y |X)(Y X) (XX))μm,t = μ(YX t − μ(X)(9)
Σmm + Σmm|X)
Y)X) (XX)
Σ(Y= Σ(Y− Σ(YΣmmmm−1)
Σ(XYm(10)Ͱ༩͑ΒΕΔɽ·ͨɼࣜ (4) ʹ͓͍ͯɼϕΫτϧ(y )(y )v (y ) = v1 , · · · , vD(y) ͸‫಺ྻܥ‬มಈʢglobal vari-ance: GVʣΛද͠ɼ࣍ࣜͰ‫͞ࢉܭ‬ΕΔɽ
(y )
vd=TT
1
1 
yt,d −yτ,dT t=1T τ =12(11)͜͜Ͱɼyt,d ͸ϑϨʔϜ t ʹ͓͚Δग़ྗ੩తಛ௃ྔϕΫτϧͷ d ࣍‫ݩ‬໨ͷཁૉΛද͢ɽGV ͷ֬཰ີ౓ؔ਺
͸ਖ਼‫ن‬෼෍ͰϞσϧԽ͞Εɼύϥϝʔληοτ λ(v)͸ฏ‫ۉ‬ϕΫτϧ μ(v) ͓Αͼ‫ڞ‬෼ࢄߦྻ Σ(v) ͔Β੒Δɽ͜ΕΒ͸ɼGMM ͱಉ༷ʹֶशσʔλ͔Βࣄલʹ‫ٻ‬ΊΔɽఆ਺ ω ͸ GV ໬౓ॏΈΛද͢ɽࣜ (4) ʹ͓͍ͯɼม‫׵‬੩తಛ௃ྔ‫ྻܥ‬ϕΫτϧ͸ɼ‫ྻܥ‬୯ҐͷόονॲཧʹΑΔ൓෮ԋࢉʹΑΓ‫ٻ‬ΊΒΕΔ͕ɼϦΞϧλΠϜม‫ॲ׵‬ཧͰ͸ɼ͞Βʹɼ࠶‫ؼ‬తղ๏ [23, 24] ʹ‫ج‬ͮ͘୹஗Ԇม‫׵‬๏ [25] ͱ GV ϙετϑΟϧλ [4] Λಋೖ͢Δ͜ͱͰɼϑϨʔϜॲཧʹΑΔۙࣅղΛ‫ٻ‬ΊΔɽ·ͣɼP Y |X, λ(X,Y ) ͷ࠷େԽΛߦ͏ɽ֤ϑϨʔϜʹ͓͍ͯɼࣜ (8) ͷࣄ‫͖ͮجʹ཰֬ޙ‬ɼࣜ (7) ͷ৚݅෇͖֬཰ີ౓ؔ਺Λ୯Ұ෼෍ m̂t Ͱۙࣅ͢Δɽ

- 1458 -m̂t

(Y |X)= arg max αm,tm(12)

2013年9月|X)·ͨɼ‫ڞ‬෼ࢄߦྻ Σ(Yͷର֯ཁૉͷΈΛ༻͍ͯɼ࣍m‫ݩ‬ຖʹಠཱʹม‫ॲ׵‬ཧΛߦ͏ɽ͜ͷ࣌ɼม‫׵‬੩తಛ௃ྔ‫ྻܥ‬͸ T ‫ݸ‬ͷ࿈ཱҰ࣍ํఔࣜͷղͱͯ͠༩͑ΒΕΔ
͕ [26]ɼΧϧϚϯϑΟϧλʹΑΔۙࣅॲཧΛಋೖ͢Δ͜ͱͰɼ୹஗ԆॲཧΛ࣮‫͢ݱ‬Δ3 ɽ(L+1) ࣍‫ݩ‬ͷग़ྗ੩తಛ௃ྔηάϝϯτϕΫτϧ y d = [yt−L,d , · · · , yt,d ]ʹର͢ΔҎԼͷঢ়ଶۭؒϞσϧΛ༻͍Δɽ
(t)(t−1)(y|X)
yd = J L yd+ 01×L , μm̂t ,t,d + nm̂t ,t,d (13)(Δy|X)(t)

μm̂t ,t,d = wL y d + em̂t ,t,d(14)͜͜Ͱɼ0N ×M ͸ N × M ͷྵߦྻΛࣔ͠ɼ(L + 1)࣍‫ߦݩ‬ϕΫτϧ wL ͱ (L + 1) × (L + 1) ߦྻ J L ͸
wL = 01×(L−1) , −1, 1

JL =0 I L×L
0 01×L(15)ਤ 1 ʹɼϦΞϧλΠϜม‫ॲ׵‬ཧͷྲྀΕΛࣔ͢ɽ֤ϑϨʔϜʹ͓͍ͯɼಛ௃ྔநग़ॲཧɼ୹஗Ԇม‫ॲ׵‬ཧ͕ߦΘΕΔɽ೾‫߹ܗ‬੒ॲཧʹ͓͍ͯ͸ɼPSOLAʢpitchsynchronous overlap and addʣ[27] ʹΑΓྭৼ‫ݯ‬೾‫ܗ‬Λੜ੒ͨ͠‫ʹޙ‬ɼεϖΫτϧแབྷύϥϝʔλΛ৞ΈࠐΉɽ෼ੳ૭௕Λ 25 ms ͱ͠ɼೖྗηάϝϯτಛ௃ྔநग़࣌ͷύϥϝʔλ C Λ 2ɼ୹஗Ԇม‫࣌׵‬ͷύϥϝʔλ L Λ 2ɼF0 ͷ࠷খ஋Λ 70 Hzʢ‫ج‬ຊप‫< ظ‬15 msʣͱͨ͠ࡍʹ͸ɼ࠷େ஗Ԇ࣌ؒ͸ 50 ms ͱͳΔɽ4Ի੠ੜ੒‫ػ‬ೳ֦ுϦΞϧλΠϜ੠࣭ม‫ॲ׵‬ཧʹΑΓɼԻ੠ίϛϡχέʔγϣϯʹ͓͚ΔԻ੠ੜ੒‫ػ‬ೳͷ֦ுΛߦ͏ɽҎԼͰ͸ɼԠ༻ྫΛ͍͔ͭ͘঺հ͢Δɽ

4.1

ແ޴಄Ի੠‫ڧ‬ௐ޴಄ఠग़ऀ͸੠ଳͷফࣦʹ൐͍ɼ৯ಓൃ੠΍ి‫ؾ‬ࣜਓ޻޴಄Λ༻͍ͨൃ੠ʹ୅ද͞ΕΔ୅ସൃ੠๏Λ
༻͍Δඞཁ͕͋Δɽ͔͠͠ͳ͕Βɼੜ੒͞ΕΔԻ੠
(y|X)(Δy|X)(y|X)(Δy|X)
ʢແ޴಄Ի੠ʣͷ඼࣭͸ɼ௨ৗԻ੠ͱൺֱͯ͠େ͖͘
Ͱɼμm̂t ,t,d ɼμm̂t ,t,d ɼΣm̂t ,d ɼΣm̂t ,d ͸ɼ֤ʑɼࣜ
ྼԽ͢Δɽͦ͜ͰɼϦΞϧλΠϜ੠࣭ม‫׵‬Λ༻͍ͯɼ(Y |X)|X)(9) ͷ μm,t ͓Αͼࣜ (10) ͷ Σ(Yʹ͓͚Δ d ࣍mແ޴಄Ի੠Λ௨ৗԻ੠΁ͱม‫͢׵‬Δ͜ͱͰɼ޴಄ఠ‫ݩ‬໨ͷ੩తɾಈతಛ௃ྔʹର͢ΔཁૉͰ͋Δɽঢ়ଶۭग़ऀͷԻ੠ੜ੒‫ػ‬ೳΛ֦ு͢Δ [28, 29]ɽೖྗಛ௃ྔ
(t)(t)
ؒͷ‫ڞ‬෼ࢄߦྻΛ P d ɼฏ‫ۉ‬ϕΫτϧΛ ŷ d ͱ͢Δɽͱͯ͠ແ޴಄Ի੠ͷεϖΫτϧηάϝϯτಛ௃ྔΛ(0)(0)֤ʑͷॳ‫ظ‬஋ P d , ŷ d Λྵߦྻ͓ΑͼྵϕΫτϧ࢖༻͢Δɽग़ྗಛ௃ྔͱͯ͠ɼ௨ৗԻ੠ͷεϖΫτϧͱͯ͠ɼ֤ϑϨʔϜʹ͓͍ͯɼࣜ (16) ͱࣜ (17) ͷ༧ಛ௃ྔͷΈͰͳ͘ɼF0 ΍ඇप‫ظ‬੒෼ͳͲͷԻ‫ݯ‬ಛ௃ଌॲཧͱɼࣜ (18) ͱࣜ (19) ͷߋ৽ॲཧΛߦ͏ɽྔͷਪఆ΋ߦ͏ɽຊॲཧʹΑΓɼແ޴಄Ի੠ͷࣗવੑ(t−1)(t−1) (y|X)Λେ෯ʹվળ͢Δ͜ͱ͕ՄೳͱͳΔɽ
Pd= J LP d
J L + diag 01×L , Σm̂t ,d (16)
4.2 αΠϨϯτԻ੠௨࿩(t−1)(t−1)(y|X)
ŷ d= J L ŷ d+ 01×L , μm̂t ,t,d(17)Ի੠ίϛϡχέʔγϣϯʹ಺ࡏ͢Δຊ࣭తͳ໰୊ͱ
(t)(t)
(t−1)
P d = I − kd w L P d(18)ͯ͠ɼ૬खʹௌऔՄೳͳԻ੠Λൃ੠͠ͳ͚Ε͹ͳΒͳ͍ͱ͍͏఺͕͋Δɽ݁Ռͱͯ͠ɼपғʹୈࡾऀ͕͍
(t)
(t−1)(t)(Δy|X)
(t−1)ŷ d = ŷ d(19)+ kd μm̂t ,t,d − wL ŷ dΔࡍʹ͸ൿಗੑͷߴ͍ձ࿩͕ࠔ೉ͱͳͬͨΓɼൃ੠ʹΑΓपғʹ໎࿭Λ͔͚ΔͳͲͱ͍ͬͨঢ়‫͕گ‬ੜ͡Δɽ
(t)͜͜Ͱɼ(L + 1) ࣍‫ݩ‬ΧϧϚϯήΠϯϕΫτϧ kd ͸͜ͷ໰୊ʹରͯ͠ɼମ಺఻ಋϚΠΫϩϗϯͷҰͭͰ͋
−1ΔඇՄௌͭͿ΍͖ʢnonaudible murmur: NAMʣϚ(t)(t−1) (Δy|X)(t−1) kd = P dwt Σm̂t ,d + wL P dwL(20)ΠΫϩϑΥϯΛ༻͍ͯɼपғ͕ௌऔࠔ೉ͳ΄Ͳখ͞ͳ੠Λऩ࿥͢Δ࿮૊Έ͕ఏҊ͞Ε͍ͯΔ [30]ɽ͔͠͠ͳ(t)Ͱ༩͑ΒΕΔɽ֤ϑϨʔϜʹ͓͍ͯɼߋ৽‫ޙ‬ͷ ŷ d ͷ͕Βɼऩ࿥͞ΕΔମ಺఻ಋԻ੠ͷ඼࣭͓Αͼ໌ྎੑҰͭ໨ͷཁૉΛɼt − L ϑϨʔϜʹ͓͚Δม‫׵‬ಛ௃ྔ͸ஶ͘͠ྼԽ͢ΔͨΊʹɼϦΞϧλΠϜ੠࣭ม‫׵‬Λ
ŷt−L,d ͱ͢ΔɽϕΫτϧ ŷ t−L ͷ d ࣍‫ݩ‬໨ͷཁૉ༻͍ͯɼମ಺఻ಋԻ੠Λ௨ৗԻ੠΁ͱม‫͢׵‬Δ [31]ɽ࣍ʹɼP v (y ) |λ(v) ͷ࠷େԽΛߦ͏ͨΊʹɼGV͜ΕʹΑΓɼ੠Λग़ͣ͞ʹಛఆͷ૬खʹରͯ͠ͷΈΛߟྀͨ͠ϙετϑΟϧλॲཧΛߦ͏ɽҙࢥ఻ୡΛߦ͏ҰछͷςϨύγʔͷΑ͏ͳԻ੠ίϛϡ1−1χέʔγϣϯ‫ܗ‬ଶ͕࣮‫͞ݱ‬ΕΔɽ
22(GV)(v)(v)
ŷt−L,d = μd μ̂d(ŷt−L,d − ŷd ) + ŷd  (21)
4.3 ϘΠεʗϘʔΧϧΤϑΣΫλ
(v)(v)
͜͜Ͱɼμd ͓Αͼ μ̂d ͸ɼग़ྗ੩తಛ௃ྔ͓ΑͼϦΞϧλΠϜ੠࣭ม‫ʹ׵‬ΑΓɼࣗ਎ͷ਎ମత੍໿Λม‫׵‬੩తಛ௃ྔͷ GV ฏ‫ۉ‬ϕΫτϧͷ d ࣍‫ݩ‬໨ͷཁ௒͑ͨ੠࣭ʹΑΔൃ੠͕ՄೳͱͳΔɽ͞Βʹɼ‫ݻ‬༗੠ૉΛද͠ɼŷd  ͸ม‫׵‬੩తಛ௃ྔͷ d ࣍‫ݩ‬໨ͷόΠม‫ٕ׵‬ज़ [32] Λಋೖ͢Δ͜ͱͰɼಛఆͷ੠࣭Λ࣋ͭΞε஋ͷฏ‫ۉ‬Λද͢ɽ͜ΕΒͷ஋͸ɼֶशσʔλΛ༻࿩ऀͷ੠ʹม‫͢׵‬Δ͚ͩͰͳ͘ɼ੠࣭Λ੍‫͢ޚ‬Δύϥ͍ͯࣄલʹ‫ٻ‬Ί͓ͯ͘ɽϝʔλΛखಈͰૢ࡞͢Δ͜ͱͰɼॴ๬ͷ੠࣭ΛੜΈग़
3 ࿈ཱҰ࣍ํఔࣜͰऔΓѻ͏ T × T ͷ‫ྻߦٯ‬ΛଳߦྻͰۙࣅ͠ɼ
͢͜ͱ΋ՄೳͱͳΔɽՎ੠ม‫ʹ׵‬΋Ԡ༻Ͱ͖ΔͨΊ(t)ϑϨʔϜຖʹଳߦྻͷཁૉʢࣜ (18) ʹ͓͚Δ P d ʹରԠʣΛ࠶[33]ɼ৽ͨͳՎএද‫͕ݱ‬ੜΈग़͞ΕΔՄೳੑ͕͋Δɽ‫ؼ‬తʹߋ৽͢ΔॲཧͱͳΔɽ
Ͱද͞ΕΔɽ·ͨɼI L×L ͸ L × L ͷ୯ҐߦྻΛࣔ͢ɽࡶԻ੒෼ nm̂t ,t,d ͓Αͼ em̂t ,t,d ͸ɼ֤ʑɼฏ‫ ۉ‬0 Ͱ෼(y|X)(Δy|X)ࢄ͕ Σm̂t ,d ͓Αͼ Σm̂t ,d ͷਖ਼‫ن‬෼෍ʹै͏ɽ͜͜

日本音響学会講演論文集- 1459 -2013年9月

Inputwaveform
Frame shift = 5 ms
Featureextraction

Low-delay
conversion

Speechparametersx t −7xt −6xt − 5x t −4xt −3x t −2

xt −1xt

Sourcefeatures
Selected
mixturecomponents

X t −7

X t− 6

X t −5X t −4

X t− 3

X t−2

X t −1

Xtmˆ t −7mˆ t −6mˆ t −5mˆ t −4mˆ t− 3mˆ t − 2mˆ t −1m̂tParametersin state space
Converted
speechparameters

Waveform
synthesis

Converted
excitation
Convertedwaveform

Fig. 15P( t −7 )yˆ(t − 7 )P( t− 6 )yˆ

( t −6 )P(t −5 )yˆ( t −5 )P( t − 4)yˆ(t − 4 )P( t −3)yˆ( t −3)

1 / Fˆ0 , t −5

Window length= 25 ms

Recursive update of state parametersm̂tP( t −1)Pyˆ(t −1)yˆ (t )

P ( t−1)

P ′ ( t−1)

P (t )yˆ ( t−1)yˆ ′( t −1)yˆ ( t)(t ))yˆ t(−GV
2

1 / Fˆ0 , t −2
Filtering
Maximum delay = 50 ms

Frame-by-frame processing in real-time voice conversion (C = 2, L = 2).

ϦΞϧλΠϜ੠࣭ม‫ٕ׵‬ज़ͱɼͦͷԠ༻ྫͰ͋ΔԻ੠ੜ੒‫ػ‬ೳ֦ுʹ͍ͭͯड़΂ͨɽະͩղܾ͢΂͖໰୊͸ଟ͘࢒͞Ε͓ͯΓɼ֎෦ࡶԻ‫ڥ؀‬΍ൃ࿩༷ࣜͷมԽ΁ͷରԠɼ੠੍࣭‫ޚ‬ͷૢ࡞ੑվળɼ஗Ԇ࣌ؒͷ࡟‫͓ݮ‬Αͼม‫׵‬ਫ਼౓ͷ޲্ͳͲʹऔΓ૊Ήඞཁ͕͋Δɽͳ͓ɼԻ੠ੜ੒‫ػ‬ೳ֦ுʹΑΓɼ͜Ε·Ͱඇ‫ޠݴ‬৘ใͱͯ͠औΓѻΘΕ͍ͯͨ΋ͷ΋ҙਤతʹ੍‫ޚ‬Մೳͱ
ͳΔɽΑΓ๛͔ͳൃ੠ද‫ݱ‬ͷ࣮‫ظ͕ݱ‬଴͞ΕΔ൓໘ɼͳΓ͢·͠౳ͷ‫ݥة‬ੑ͸૿͢ɽຊٕज़͕΋ͨΒ͢ར఺ͱ‫ݥة‬ੑͷ྆໘ʹਅ᎜ͳ໨Λ޲͚ɼࣾձతʹਖ਼ٕ͘͠ज़͕ೝ஌͞ΕΔΑ͏౒ΊΔ͜ͱ͕ॏཁͰ͋Δɽँࣙ ຊ‫ڀݚ‬ͷҰ෦͸ɼՊ‫ݚ‬අิॿۚएख‫ڀݚ‬ʢ̖ʣʹΑΓ࣮ࢪͨ͠΋ͷͰ͋Δɽ

[1] Abe et al., J. Acoust. Soc. Jpn. (E), 11(2), 71–76, 1990.
[2] Stylianou et al., IEEE Trans. Speech & Audio
Process., 6(2), 131–142, 1998.
[3] Toda et al., IEEE Trans. Audio, Speech &Lang. Process., 15(8), 2222–2235, 2007.
[4] Toda et al., Proc. INTERSPEECH, 2012.
[5] Narendranath et al., Speech Commun., 16(2),207–216, 1995.
[6] Takashima et al., Proc. SLT, 313–317, 2012[7] தࣛ ଞ, Իߨ࿦, 517–520, Mar. 2013.
[8] Zen et al., Speech Commun., 51(11), 1039–1064, 2009.
[9] ٢ଜ ଞ, ৴ֶ࿦ʢD–IIʣ, J83–D–II(11), 2099–2107, 2000.
[10] Gales, Computer Speech & Lang., 12(2), 75–98, 1998.
[11] Gauvain and Lee, IEEE Trans. Speech & Audio
Process., 2(2), 291–298, 1994.
[12] Yamagishi and Kobayashi, IEICE Trans. Inf. &Syst., E90-D(2), 533–543, 2007.

日本音響学会講演論文集yˆ( t− 2 )xt + 2))))))yˆ t(−GVyˆ t(−GVyˆ t(−GVyˆ t(−GVyˆ t(−GVyˆ t(−GV765432͓ΘΓʹࢀߟจ‫ݙ‬P(t − 2)xt +1[13] Kuhn et al., IEEE Trans. Speech & Audio Process., 8(6), 695–707, 2000.
[14] Shichiri et al., Proc. INTERSPEECH, 1269–1272, 2002.
[15] Nose et al., IEICE Trans. Inf. & Syst., E90D(9), 1406–1413, 2007.
[16] Tao et al., IEEE Trans. Speech & Audio Process., 14(4), 1145–1154, 2006.
[17] Wu et al., IEEE Trans. Speech & Audio Process., 18(6), 1394–1405, 2010.
[18] Inanoglu et al., Speech Commun., 51(3), 268–283, 2010.
[19] த໺, ‫ޙ‬౻, ৘ॲֶ࿦, 52(12), 3853–3867, 2011.
[20] Nose et al., IEICE Trans. Inf. & Syst., E93D(9), 2483–2490, 2010.
[21] Kawahara et al., Speech Commun., 27(3–4),
187–207, 1999.
[22] Kain and Macon, Proc. ICASSP, 285–288,
1998.
[23] ಙా ଞ, Ի‫ࢽڹ‬, 53(3), 192–200, 1997.
[24] Koishida et al., IEICE Trans. Inf. & Syst., E84D(10), 1427–1434, 2001.
[25] Muramatsu et al., Proc. INTERSPEECH,1076–1079, 2008.
[26] Tokuda et al., Proc. ICASSP, 1315–1318, 2000.
[27] Moulines and Charpentier, Speech Commun.,9(5–6), 453–467, 1990.
[28] Doi et al., IEICE Trans. Inf. & Syst., E93D(9), 2472–2482, 2010.
[29] Nakamura et al., Speech Commun., 54(1), 134–146, 2012.
[30] தౡ ଞ, ৴ֶ࿦, J87-D-II(9), 1757–1764, 2004.
[31] Toda et al., IEEE Trans. Speech & Audio Process., 20(9), 2505–2517, 2012.
[32] ‫ాށ‬, Իߨ࿦, 1-8-11, 257–260, Sep. 2011.
[33] Doi et al., Proc. APSIPA ASC, 2012.

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