1-8-7
DOA-HMM ʹͮ͘جҠಈԻݯͷྼܾఆϒϥΠϯυԻݯ ∗
ˑඉ࠸ޱɼߴफయݰɼதଜ༑ɼُԬ߂ (౦େใཧ)
1
पղΛ༻͍ΔͱɼΈࠐΈࠞ߹Λۙࣅతʹॠ
͡Ίʹ
࣌ࠞ߹Ͱද͢͜ͱ͕Ͱ͖Δɻ͜ͷ؍ଌ৴߸Ϟσϧʹ
ຊߘͰɼҠಈԻݯΛରͱͨ͠ྼܾఆϒϥΠϯυ
ԻݯͷΛѻ͏ɻϒϥΠϯυԻݯ (Blind
Source Separation; BSS) ͱɼԻ͔ݯΒ؍ଌ৴߸·
Ͱͷୡಛੑ͕ະͰ͋Δ߹ʹɼෳͷԻ͕ࠞ
߹ͨ͠৴߸͔ΒݩͷԻ৴߸Λ͢Δٕज़Ͱ͋Δɻ
ྫ͑ɼձٞʹ͓͍ͯෳͷԻ৴߸ͷࠞͬͨ͡Ի
σʔλ͔ΒձٞΛࣗಈ࡞ͨ͠ΓɼϩϘοτʹपғ
ͷԻڥΛೝࣝ͢ΔػೳΛඋ͑ͤ͞Δ༻్ͷԠ༻
͕ظ͞Ε͍ͯΔɻ
BSS Ͱ؍ଌ৴߸͔ΒԻݯ৴߸ͱͦͷࠞ߹աఔΛ
ਪఆ͢Δඞཁ͕͋ΔͨΊɼ௨ৗԻݯͦͷࠞ߹աఔ
ʹରͯ͠ԿΒ͔ͷԾఆΛஔ͖ɼͦͷԾఆʹΑΓཱͯΒ
ΕΔن४ΛͱʹະมΛਪఆ͢Δ࠷దԽͱ
ͯ͠ఆࣜԽ͞ΕΔɻྫ͑ɼBSS ʹ͓͍ͯ؍ଌ৴߸
͕ԻݯΑΓଟ͍༏ܾఆͰɼԻݯ৴߸ؒͷಠ
ཱੑΛԾఆͯ͢͠Δಠཱੳ (Independent
Component Analysis; ICA) ͕༗༻Ͱ͋Δ͜ͱ͕Β
Ε͓ͯΓɼԻݯ৴߸ؒͷಠཱੑΛ࠷େԽ͢ΔΑ͏ʹ
ϑΟϧλΛਪఆ͢Δ͜ͱ͕తͱͳΔ [1]ɻ͔͠͠ɼ
ICA Ͱ؍ଌ৴߸͕ԻݯΑΓগͳ͍ྼܾఆ
Λѻ͏͜ͱͰ͖ͣɼ͜ͷ߹ಠཱੑΑΓ͞Β
ʹ͍ڧԾఆ͕ඞཁͰ͋Δɻ
ԻΛରͱͨ͠ྼܾఆ BSS ͰɼԻͷ࣌ؒप
ͷεύʔεੑΛར༻ͨ͠Ξϓϩʔν͕༗ޮ
Ͱ͋Δ͜ͱ͕ΒΕ͍ͯΔ [2–9]ɻԻͷεύʔεੑ
ͱɼԻ৴߸ͷ࣌ؒप͕΄ͱΜͲͷ࣌ؒ
पʹ͓͍ͯ΄΅ 0 ͱͳΔੑ࣭Ͱ͋Δɻ͜ͷੑ
࣭ʹΑΓɼෳͷԻ͕ಉ࣌ʹൃ͞Εͨঢ়Ͱگɼ
֤Իͷ༏ͳ࣌ؒप͕ͱ΄ʹ͍ޓΜͲॏ
ͳΓ߹Θͳ͍ͱԾఆͰ͖Δ߹͕ଟ͍ɻΑͬͯɼνϟ
ωϧؒͷҐ૬ৼ෯ͷҧ͍Λखֻ͔Γͱ֤ͯ࣌͠
ؒपͰͲͷԻ࠷͕ݯ༏Β͍͔͠ΛਪఆͰ
͖ΕɼతͷԻ৴߸ͷΈΛ௨աͤ͞Δ࣌ؒप
ϚεΫΛઃ͢ܭΔ͜ͱͰ৴߸ΛಘΔ͜ͱ͕Ͱ
͖Δɻ
Ҏ্ͷԻͷεύʔεੑΛ؍ଌ৴߸ͷϞσϧʹ
ΈࠐΉͨΊʹɼ؍ଌ৴߸ͷϞσϧΛ࣌ؒपྖ
ҬͰఆࣜԽ͢Δඞཁ͕͋Δɻ௨ৗɼ֤ϚΠΫϩϑΥϯ
ͷ؍ଌ৴߸Իݯ৴߸ͷ࣌ؒΕΛؚΉΈࠐΈࠞ
߹Ͱද͞ΕΔ͕ɼԻ͔ݯΒϚΠΫϩϑΥϯ·ͰͷΠϯ
ύϧεԠʹରͯ͠ेʹ͍࣌ؒ૭Λͭ࣌ؒ
∗
ͮ͘جBSS पྖҬ BSS ͱݺΕɼ࣌ؒྖҬͷ
BSS ʹରͯ͠ԋࢉྔͷগͳ͍ΞϧΰϦζϜΛ࣮Ͱݱ
͖ΔɼԻͷεύʔεੑΛΈࠐΊΔͳͲಛ
͕͋ΔҰํͰɼप͝ͱʹͨ͠৴߸ΛԻݯ
͝ͱʹάϧʔϐϯά͢Δύʔϛϡςʔγϣϯ߹ͱݺ
ͿΛղܾ͢Δඞཁ͕͋Δɻ
ຊڀݚͷతɼ֤Ի͕ݯҠಈͨ͠߹ʹԻݯ
ҐஔΛ͠ͳ͕ΒదʹԻݯΛߦ͑Δख๏Λ
࣮͢ݱΔ͜ͱͰ͋ΔɻզʑҎલɼԻݯ౸དྷํΛ
ࢄͷજࡏมͱѻ͍ɼͦͷࠞ߹ϞσϧʹΑΓ֤Իݯ
ͷεςΞϦϯάϕΫτϧΛ֬ϞσϧԽ͠ɼ؍ଌ৴߸
ͷੜϞσϧʹΈࠐΉ͜ͱͰύϥϝʔλਪΛ௨
ͯ͠ύʔϛϡςʔγϣϯ߹ͱपྖҬ BSS Λಉ
࣌ʹߦ͏ΞϓϩʔνΛఏҊͨ͠ [8] (ͳ͓ɼ΄΅ಉ࣌
ʹظେ௩ΒʹΑͬͯྨࣅͨ͠Ξϓϩʔν͕ఏҊ͞
Ε͍ͯΔ [9])ɻຊߘͰ͜ΕΛ֦ு͠ɼ࣌ؒมԽ͢Δ
֤ԻݯͷεςΞϦϯάϕΫτϧΛɼࢄԽ͞Ε֤ͨ֯
Λঢ়ଶͱ͢ΔӅΕϚϧίϑϞσϧ (Hidden Markov
Model; HMM) ʹΑΓ֬ϞσϧԽ͠ɼ؍ଌ৴߸ͷੜ
ϞσϧʹΈࠐΈɼύϥϝʔλਪΛ௨ͯ͠ύʔ
ϛϡςʔγϣϯ߹ɼ֤ҠಈԻݯͷ౸དྷํɼप
ྖҬ BSS Λಉ࣌ʹߦ͏ख๏ΛఏҊ͢Δɻ
2
؍ଌϞσϧ
I ݸͷԻ͔ݯΒ౸དྷ͢Δ৴߸Λ M ݸͷϚΠΫϩ
ϑΥϯͰ؍ଌ͢Δ߹Λߟ͑ɼm ൪ͷϚΠΫϩϑΥ
ϯͰ؍ଌ͞ΕΔ৴߸ͷ࣌ؒपΛ ym (ωk , tl )ɼ
i ൪ͷԻݯ৴߸ͷ࣌ؒपΛ si (ωk , tl ) ͱ
͠ɼy(ωk , tl ) = (y1 (ωk , tl ), . . . , yM (ωk , tl ))T ∈ CM ,
s(ωk , tl ) = (s1 (ωk , tl ), . . . , yI (ωk , tl ))T ∈ CI ͱ͢Δɻ
ͨͩ͠ɼ1 ≤ k ≤ K, 1 ≤ l ≤ L ࣌ؒपྖҬʹ
͓͍ͯͦΕͧΕप͓Αͼ࣌ؒʹରԠ͢ΔΠϯσο
ΫεͰ͋Δɻઌʹड़ͨ௨Γɼ࣌ؒपྖҬʹ͓͍
ͯ؍ଌ৴߸ y(ωk , tl ) ۙࣅతʹ
y(ωk , tl ) =
I
X
ai (ωk )si (ωk , tl ) + n(ωk , tl )
(1)
i=1
ͷΑ͏ʹ s1 , . . . , sI ͷॠ࣌ࠞ߹ͷͰܗද͢͜ͱ͕Ͱ
͖Δɻ͜͜Ͱɼai (ωk ) Ի ݯi ͷεςΞϦϯά (ํ
) ϕΫτϧΛද͠ɼ͜ΕΛฒͨߦྻ A(ωk ) =
Underdetermined blind separation of moving sound sources based on DOA-HMM. by HIGUCHI Takuya,
TAKAMUNE Norihiro, NAKAMURA Tomohiko, KAMEOKA Hirokazu (Graduate School of Information
Science and Technology, The University of Tokyo)
日本音響学会講演論文集
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2013年9月
(a1 (ωk ), . . . , aI (ωk )) ∈ CM ×I Λࠞ߹ߦྻͱͿݺɻ
n(ω, t) എࡶܠԻϑϨʔϜΛ͑Δڹͳ
ͲͰ͋ΔɻԻͷεύʔεੑΛԾఆ͠ɼ֤࣌ؒप
(ωk , tl ) ʹ͓͍ͯΞΫςΟϒͰ͋ΔԻݯͷΠϯσο
ΫεΛ zk,l ∈ {1, . . . , I} ͱද͢ͱɼࣜ (1)
y(ωk , tl ) = azk,l (ωk )s(ωk , tl ) + n(ωk , tl )
(2)
Δɻͦ͜ͰɼԻ ݯi ͷ౸དྷํ θi ͕طͷͱ͖ɼai,k
h(θi , ωk ) Λฏͨ͠ͱۉෳૉਖ਼نΑΓੜ͞Ε
ΔͱԾఆ͢Δɻ͔͠͠વͳ͕Β౸དྷํ θi ࣮ࡍ
ʹ؍ଌ͢Δ͜ͱ͕Ͱ͖ͳ͍ͨΊɼ͜ΕΛજࡏม
͢ʹͱ͜͢ͳݟΔͱɼai,k ͷੜϞσϧ DOA Λજ
ࡏมͱͨࠞ͠߹ϞσϧͱͳΔɻ͜ΕΛ 3.1 અͷੜ
ϞσϧʹΈࠐΈɼੜϞσϧશମͷύϥϝʔλਪ
Λߦ͏͜ͱɼύʔϛϡςʔγϣϯ߹ɼ֤Իݯͷ
ͷΑ͏ʹॻ͖ͤΔɻ͜ͷ؍ଌϞσϧ͓͍ͯɼ֤
࣌ؒपʹ͓͍ͯ zk,l ൪ͷԻݯҎ֎ͷ
ͯ͢ 0 ͱԾఆ͞Εͨ͜ͱʹͳΔɻै֤ͬͯ࣌ؒप
ͰԻݯΛද͢ม zk,l ͷΈͰेͰ͋Γɼ
͜ͷͨΊ্ࣜͰ si (ωk , tl ) ͷΠϯσοΫε i Λল͍
͍ͯΔɻ͢ͳΘͪ s(ωk , tl ) ֤࣌ؒपʹ͓͍
ͯΞΫςΟϒͳ͍ͣΕ͔ͷԻݯͷΛද͢มͱ
ͳΔɻҎࢴޙ໘ͷεϖʔεͷઅͷͨΊɼωk ͱ tl Λ
Լ͖ఴ͑ࣈ k, l Ͱද͢هΔ͜ͱʹ͢Δɻ
DOA ਪఆɼप͝ͱͷԻݯΛڠௐతʹߦ͏͜
ͱʹ૬͢Δ [8]ɻ
·ͣɼϑ1 , . . . , ϑD (ͯ͢ఆ) ͔ΒͳΔ D ݸͷ
DOA ީิͷू߹Λ༻ҙ͢Δɻྫ͑ 180 Λ D
ͨ֯͠ ϑd = (d − 1)π/D, (d = 1, . . . , D) ͷू߹
Λߟ͑Δɻ֤Իݯͷ DOA ͕͜ͷ DOA ީิͷத͔
Βܾఆ͞ΕΔͱԾఆ͢ΔͱɼԻ ݯi ͷ౸དྷํ θi ͕
ੜ͞ΕΔϓϩηεҎԼͷΑ͏ʹهड़Ͱ͖Δɻ
ci |ρi ∼ Categorical(ci ; ρi )
3
(5)
ੜϞσϧ
θ i = ϑc i
3.1
(6)
؍ଌ৴߸ͷੜϓϩηε
؍ଌϞσϧΛͱʹɼ؍ଌ৴߸͕ੜ͞ΕΔϓϩ
ηεΛੜϞσϧʹΑΓهड़͢Δɻ
(n)
·ͣɼࡶԻ nk,l ͕ɼฏ ͕ۉ0ɼڞࢄ͕ Σk
ͷෳૉਖ਼نʹै͏ͱԾఆ͢Δͱɼ͠ a1:I,k =
{a1,k , . . . , aI,k } ,sk,l ͓Αͼ zk,l ͕طͰ͋Εɼࣜ
(2) ΑΓ yk,l
(n)
yk,l |a1:I,k,l , sk,l , zk,l ∼ NC (azk,l ,k sk,l , Σk )
(3)
P
yd = 1 ͱ͢Δ
ͱɼCategorical(x; y) ∝ yx Ͱ͋Δɻ·ͨɼρi =
(ρi,1 , . . . , ρi,D ) Ͱ͋Δɻci ∈ {1, . . . , D} i ൪ͷ
ԻͲʹݯͷ DOA ީิׂ͕ΓͯΒΕΔ͔Λද͢
ΠϯδέʔλมͰ͋Γɼ্ࣜ͜Ε͕ࢄ (֤
͕֬ ρi,1 , . . . , ρi,D ) ͔Βੜ͞ΕΔ͜ͱΛҙຯ͠
͍ͯΔɻ͜ͷϓϩηεʹΑΓ֤Իݯͷ DOA ͕ܾఆ͞
Εɼୡपಛੑ ai,k
ͨͩ͠ɼy = (y1 , . . . , yD ),
d
(a)
ʹΑΓੜ͞ΕΔɻ͜͜Ͱɼzk,l Λࢄͷજࡏมͱ
ai,k |ci ∼ NC (ai,k ; h(ϑci , ωk ), Σk )
ͤͳݟɼyk,l ͷ֬ࠞ߹ਖ਼نͱͳΔ [6,7]ɻ
ઘΒɼ͜ͷ֬Ϟσϧʹ͖ͮجɼExpectation-
ʹΑΓੜ͞ΕΔɻ
Maximization (EM) ΞϧΰϦζϜʹΑΓ࠷ͷ࣌ؒप
ϚεΫΛਪఆ͢ΔΞϓϩʔνΛఏҊ͍ͯ͠Δ [6]ɻ
3.3
(7)
DOA-HMM
Ի͕ݯҠಈ͢Δ߹ɼ࣌ࠁ͝ͱʹεςΞϦϯάϕ
3.2
ࠞ߹ DOA Ϟσϧ [8]
Ϋτϧ͕มԽͯ͠͠·͏ͨΊɼҠಈԻݯΛѻ͑ΔΑ
ຊઅͰ·ͣԻݯҐஔ͕ݻఆͷ߹Λߟ͑ɼ࣍અ
ͰԻ͕ݯҠಈ͢Δ߹Λߟ͑Δɻ͜Ε·Ͱ֤Իݯͷ
͏ʹ͢ΔͨΊʹ ai,k Λ࣌ࠁ l ʹґଘ͢Δม ai,k,l
ʹ֦ு͢Δඞཁ͕͋Δɻ͜ͷͱ͖ɼࣜ (2)
ୡपಛੑ ai,k ΛपΠϯσοΫε k ͝ͱʹ
yk,l = azk,l ,k,l sk,l + nk,l
(8)
ಠཱͳมͰ͋Δ͔ͷΑ͏ʹѻ͍͕ͬͯͨɼ֤͠Ի
͕ݯ୯Ұํ͔Βฏ໘ͱͯ͠౸དྷ͢ΔͱԾఆͰ͖
ͱॻ͖ͤΔɻ
ΔͳΒɼྫ͑ϚΠΫϩϑΥϯ͕ 2 ͷ߹ɼୡ
͜͜Ͱɼ3.2 અͷࣗવͳ֦ுͱͯ͠ɼ֤Իݯͷ DOA
पಛੑ ai,k ɼ౸དྷํ (Direction-of-Arrival;
ΠϯσοΫε ci Λ࣌ࠁ l ʹґଘ͢Δม ci,l ʹ֦ு
DOA)θ ͷؔͱͯ͠
͠ɼci,1 , . . . , ci,L Λঢ়ଶ ͨ͠ͱྻܥHMM ʹΑΓες
h(θ, ω) =
"
1
eωB cos θ/C
#
ΞϦϯάϕΫτϧ ྻܥai,k,1 , . . . , ai,k,L Λ֬Ϟσϧ
(4)
Խ͢Δ͜ͱΛߟ͑Δɻ͜ͷͱ͖ɼԻ ݯi ͷ࣌ࠁ l ʹ͓
͚Δ DOAθi,l ͷੜϓϩηεɼ
ͱͯ͠ཅʹද͞ΕΔɻͨͩ͠ɼ0 ≤ θ ≤ 2π ɼB ΛϚΠ
ΫϩϑΥϯͷִؒ (m)ɼC ΛԻ (m/s) ͱ͢Δɻ࣮ࡍ
ʹڹ࣌ؒपྖҬͷॠ࣌ࠞ߹ۙࣅͳͲʹΑ
ci,l |ci,l−1 ∼ Categorical(ci,l ; ρci,l−1 )
θi,l = ϑci,l
(9)
(10)
Γɼai,k ্هͷཧ͔ࣜΒҳ͢Δ͜ͱ͕༧͞Ε
日本音響学会講演論文集
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2013年9月
ᥦἲ
ᚑ᮶ἲ
1, . . . , D ͷભҠ֬Λද͠ɼρd,d′ Λཁૉͱ͢Δ D ×
D ߦྻ ρ = (ρd,d′ )D×D ΛભҠߦྻͱ͍͏ɻ࣮ࡍͷҠ
ಈԻݯɼे͍࣌ؒͷؒʹେ͖͘౸དྷํΛม
͑ΔՄೳੑ͍ͱߟ͑ΒΕΔͷͰɼྡ͢Δঢ়ଶ
ͷભҠ֬ΛߴΊʹઃఆ͢Εྑ͍ɻ
Ҏ্ͷεςΞϦϯάϕΫτϧྻܥͷ֬ϞσϧΛ
3.1 અͷϞσϧ (ͷ࣌ม൛) ʹΈࠐΈɼશମͷύϥ
ϝʔλਪ (ޙड़) Λ௨ͯ͠ύʔϛϡςʔγϣϯ߹ɼ
ҠಈԻݯͷैɼप͝ͱͷԻݯΛಉ࣌ʹߦ
͓͏ͱ͍͏ͷ͕ఏҊख๏ͷཁͰ͋Δɻ
4
มਪΞϧΰϦζϜ
؍ଌ৴߸ Y = y1:K,1:L ͕༩͑ΒΕͨͱͰɼҎ
্ͷੜϞσϧͷύϥϝʔλ A = a1:I,1:K,1:L , S =
s1:K,1:L , Z = Z1:K,1:L , C = c1:K,1:L ͷࣄޙ
p(A, S, Z, C|Y ) ΛٻΊ͍ͨɻ͜ͷࣄޙΛղੳత
ʹಘΔ͜ͱ͍͕͠ɼมਪ๏ʹࣅ͖ۙͮج
Λ෮ʹࢉܭΑΓಘΔ͜ͱ͕Ͱ͖ΔɻҎԼͰɼρ,
(n)
(a)
Σ1:K , Σ1:K ࣮ݧతʹఆΊΔఆͱ͢Δɻ
มਪࣄޙ p(A, S, Z, C|Y ) ͱɼ
Z
Z
· · · q(A, S, Z, C)dA · · · dC = 1
(11)
Λ ຬ ͨ ͢ ඇ ෛ ͷ ม ؔ q(A, S, Z, C) ͱ ͷ ؒ ͷ
Kullback-Leibler μΠόʔδΣϯε
p(A, S, Z, C|Y )
F[q] = log
q(A, S, Z, C) q(A,S,Z,C)
(12)
Λ q ʹؔͯ͠࠷খԽ͢Δ͜ͱ͕తͱͳΔɻͨͩ͠
R
hf (x)iq(x) q(x)f (x)dx Λද͢ɻແɼF[q] p =
q ͷͱ͖࠷খͱͳΔ͕ɼq ʹؔͯ͠
q(A, S, Z, C) = q(A)q(S)q(Z)q(C)
(13)
ͱͳΔΑ͏ͳΫϥεΛߟ͑ɼF[q] Λ q(A), q(S),
q(Z), q(C) ʹ͍ͭͯަ࠷ʹޓখԽ͢ΔεςοϓΛ܁Γ
ฦ͢͜ͱͰɼ֘ΫϥεͷதͰ p(A, S, Z, C|Y )
Λ࠷ྑۙ͘ࣅ͢ΔΛಘΑ͏ͱ͍͏ͷ͕มਪ
๏ͷجຊతͳߟ͑ํͰ͋Δɻ
ಋग़লུ͢Δ͕ɼࣜ (12) Λࣜ (11) ͷ߆ଋͷԼͰ
࠷খԽ͢Δ֤ q ղੳతʹҎԼͷ·ٻͯ͠ͱܗΔɻ
Y
q̂(A) =
NC (ai,k,l ; mi,k,l , Γi,k,l )
(14)
6,5>G%@
ͱදͤΔɻρd = (ρd,1 , . . . , ρd,D ) ঢ়ଶ d ͔Βঢ়ଶ
q̂(S) =
NC (sk,l ; µk,l , σk,l )
Y
㛫>V@
͍ͯ Forward-Backward ΞϧΰϦζϜΛߦ͏͜ͱͰ
q̂(C) ΛٻΊΔ͜ͱ͕Ͱ͖Δɻ
Ҏ্ͷมਪΞϧΰϦζϜʹΑͬͯਪఆ͞Εͨ
sk,l ͷฏۉ µk,l ʹ֬ φk.l Λ͡Δ͜ͱͰɼԻ
ݯi ͷਪఆ৴߸ΛಘΔ͜ͱ͕Ͱ͖Δɻ
5
ෳҠಈԻݯͷ࣮ݧ
ఏҊ๏ͷ༗ޮੑΛࣔͨ͢ΊɼҠಈԻʹݯରͯ͠Իݯ
ͱ౸དྷํਪఆੑೳͷূݕΛߦͬͨɻҠಈԻͱݯ
ͯ͠ҠಈԻݯσʔλϕʔε [9] ͷஉੑऀͷԻ৴߸
2 ͭΛ (ҠಈԻ ݯAɼB)ɼݻఆԻͯ͠ͱݯԻσʔλ
ϕʔε [10] ͷঁੑऀͷԻ৴߸ʹࣨΠϯύϧε
ԠΛΈࠐΈՃࢉͨ͠ͷ 1 ͭΛ༻͍ɼͦΕΒΛ
ਓతʹࠞ߹ͨ͠ͷΛ؍ଌ৴߸ͱͨ͠ɻؒ࣌ڹ
0 ms Ͱ͋ΔɻҠಈԻݯΛม͑Δ͜ͱͰɼ10 ௨Γͷࠞ
߹ԻσʔληοτΛ࡞͠ɼ࣮ͨ͠ݧɻඪຊԽप
16 kHz ͱͨ͠ɻ࣌ؒϑʔϦΤม( ϑϨʔϜ
64 msɼϑϨʔϜγϑτ 16 ms) ʹΑΓࢉग़͠
(n)
(a)
ͨɻΣk ͱ Σk ͦΕͧΕ I ɼ101.5 × I ͱͨ͠ɻ·
ͨ֯ͷׂ M = 180 ͱͨ͠ɻ4 ষͷ෮Ξϧ
ΰϦζϜͷ࣮ߦޙɼԻݯͷਪఆ µk,n ʹɼԻݯ
i ͕࣌ؒपͰͲΕ͚ͩΞΫςΟϒΒ͍͔͠Λද
֬͢ φi,k,n Λͨ͡ͷΛɼԻ ݯi ͷਪఆ࣌ؒप
ͱͨ͠ɻԻݯੑೳͷධՁج४ͱͯ͠ɼࣜ
(17)ʙ(19) ʹΑΓಋग़͞ΕΔ Signal-to-InterferenceRatio (SIR) [12] Λ༻͍ͨɻSIR ͷʹࢉܭɼ3 ͭͷ
Իݯͷ͏ͪҰ൪͍͞ͷԻ͕ݯऴྃ͢Δ 3.1 s ·
ͰΛ༻͍ͨɻ
SIRi [l] = OutputSIRi [l] − InputSIRi [l]
X
ŝi,k,l
OutputSIRi [l] = 10 log10 XkX
(15)
[dB]
(18)
si,k,l
k
InputSIRi [l] = 10 log10 X X
(16)
si′ ,k,l
[dB]
(19)
i′ 6=i k
k,l
ͳ͓ɼҎ্ͷߋ৽ଇ [8] ͱಉ༷Ͱ͋Δɻ·ͨಘΒ
Εͨ q̂(A) ʹΑͬͯ A ͷظΛ ͠ࢉܭρ Λ༻
日本音響学会講演論文集
ŝi′ ,k,l
(17)
i′ 6=i k
XX
i
q̂(zk,l ), q̂(zk,l = i) = φi,k,l
Fig. 1 ఏҊ๏ͱैདྷ๏ʹ͓͚ΔҠಈԻ ݯA ʹର͢
Δ SIR ͷ࣌ؒมԽ
k,l
q̂(Z) =
i,k,l
Y
ͨͩ͠ ŝi,k,n Ի ݯi ͷਪఆ৴߸ φi,k,n µk,n ʹ·ؚ
ΕΔԻ ݯi ͷ৴߸Ͱ͋Δɻ
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2013年9月
6,5>G%@
฿᮶ゅᗘ>UDG@
ᥦἲ
ᚑ᮶ἲ
⛣ື㡢※$┿್
⛣ື㡢※%┿್
ᅛᐃ㡢※┿್
⛣ື㡢※$᥎ᐃ್
⛣ື㡢※%᥎ᐃ್
ᅛᐃ㡢※᥎ᐃ್
⛣ື㡢※$
Fig. 2
ۉ
⛣ື㡢※%
ᅛᐃ㡢※
ఏҊ๏ͱैདྷ๏ʹ͓͚ΔԻͱ͝ݯͷ SIR ͷฏ
㛫>V@
Fig. 3 ֤Ի͚͓ʹݯΔ౸དྷ֯ͷਅͱਪఆ
·֤ͨ࣌ࠁͷ౸དྷ֯ͷਪఆʹɼਪఆ͞Εͨ
ζϜͷ࣮ݱΛࢦͨ͠ɻԻͷ࣌ؒपͷε
౸དྷ֯ͷ͔֬Β֤࣌ࠁʹ͓͍ͯ࠷֬
ύʔεੑʹͮ͘جपྖҬͷྼܾఆ BSS ϞσϧΛ
ͷߴ͍֯Λ༻͍ͨɻ
ϕΠζతʹهड़͠ɼԻݯͷҠಈΛɼࢄԽͨ͠౸དྷ֯
͞ΒʹԻݯͷҠಈΛԾఆ͠ͳ͍ैདྷ๏͕ɼҠಈԻݯ
ʹରͯ͠ྑ͍ੑೳΛͨͳ͍͜ͱΛࣔͨ͢Ίɼ[8]
Λঢ়ଶͱ͢ΔӅΕϚϧίϑϞσϧͱͯ͠ද͠ݱɼ
͍࣌ؒʹ͓͍ͯԻݯͷ౸དྷ͕֯େ͖͘มԽ͢Δ֬
ͷख๏Λ༻͍ͯಉ༷ͷԻݯ࣮ݧΛߦͬͨ߹ͷ
খ͍͞ͱ͍͏ԾఆΛભҠ֬ͱͯ͠؍ଌ৴߸ͷ
݁ՌͱఏҊ๏ͷ݁ՌΛൺֱͨ͠ɻ
Fig. 1 ʹఏҊ๏ͱैདྷ๏ʹΑΔɼ1 ͭͷ࣮ʹݧ
͓͚ΔҠಈԻ ݯA ͷ SIR ͷ࣌ؒมԽΛࣔ͢ɻैདྷ๏
ͰɼԻݯ͕͏·͘ߦ͓͑ͯΒͣɼSIR ͕ଟ͘ͷ
࣌ࠁͰ 0 ʹ͍ۙͰ͋Δ (input ͱ output Ͱ SIR ͕
վળ͞Ε͍ͯͳ͍) ͷʹରͯ͠ɼఏҊ๏Ͱଟ͘ͷ࣌
ࠁͰ SIR ͕վળ͞Ε͍ͯΔͷ͕ͯݟऔΕΔɻFig. 2 ʹ
֤Իʹͱ͝ݯσʔληοτͱ࣌ࠁͰฏۉΛͱͬͨ SIR
ͷΛࣔ͢ɻ3 ͭͷԻ͍͓ͯʹͯ͢ݯɼैདྷ๏Ͱ
SIR ͕͘Իݯ͕ߦ͍͑ͯͳ͍ͷʹରͯ͠ɼఏҊ
๏Ͱ SIR ͕ 10 dB ͔Β 17 dB ఔͷΛ͍ࣔͯ͠
Δͷ͕Θ͔Δɻ3 ͭͷԻ͚͓ʹݯΔ SIR ͷฏۉɼ
ैདྷ๏Ͱ 1.91 dBɼఏҊ๏Ͱ 12.31 dB Ͱ͋ͬͨɻ
࣍ʹɼ1 ͭͷ࣮͚͓ʹݧΔ౸དྷ֯ਪఆͷ݁Ռ
Λ Fig. 3 ʹࣔ͢ɻ࣮ࡍͷ౸དྷ֯ͱൺͯɼ1 s ۙ
͔ΒԻݯಉ࢜ͷ౸དྷ͕֯ॏͳΓɼ͔ͭԻͷऴྃ͢
Δ 3 s ۙ·Ͱɼ͓͓ΉͶਖ਼͘͠ਪఆ͞Ε͍ͯΔ͜
ͱ͕͔Δɻ࠷ॳͷ 1 s ͷؒͰ౸དྷํਪఆͷਫ਼
͕ྑ͘ͳ͍ͷɼੜϞσϧʹΈࠐ·Εͨɼ౸དྷ֯
͕ʹٸมԽ͠ʹ͍͘ͱ͍͏ԾఆʹΑΓɼԻͷೖͬ
͍ͯͳ͍ॳۙࠁ࣌ظͷσʔλʹରͯ͠ਪఆ͞Εͨ
౸དྷ͔֯ΒΒ͔ʹͭͳ͙Α͏ʹ౸དྷ͕֯ਪఆ
͞Εͯ͠·͏͔ΒͰ͋Δͱߟ͑ΒΕΔɻݻఆԻݯͷਪ
ఆ֯ʹόΠΞε͕ͷ͍ͬͯΔͷɼཧతͳεςΞ
ϦϯάϕΫτϧͱ࣮ࡍͷεςΞϦϯάϕΫτϧͱͷ
͔ࠩޡΒ͘Δਪఆ͋ͰࠩޡΔՄೳੑ͚ͩͰͳ͘ɼ[11]
ͷσʔλϕʔε࡞࣌ͷϚΠΫϩϑΥϯͷ֯ࠩޡ
Ͱ͋ΔՄೳੑߟ͑ΒΕΔɻ
6
ੜϞσϧʹΈࠐΈɼࠞ߹ DOA ϞσϧͱΈ߹Θ
ͤΔ͜ͱͰɼԻݯͱप͝ͱɼ࣌ؒ͝ͱͷύʔ
ϛϡςʔγϣϯ߹Λಉ࣌ʹ࣮ͨ͠ݱɻ͜ΕʹΑΓɼ
࣌ؒมԽ͢Δ౸དྷ֯ͷਪఆͱԻݯΛҰߦʹڍ
͑Δ͜ͱ͕ɼఏҊ๏ͷओཁͳಛͰ͋Δɻ
ࢀߟจݙ
[1] A. Hyvärinen, J. Karhunen, and E. Oja, Independent Component Analysis, John Wiley &
Sons, 2001.
[2] Ö. Yılmaz & S. Rickard, IEEE Trans. SP,
52(7), pp. 1830–1847, 2004.
[3] Y. Mori et al., in Proc. IWAENC ’05, pp. 229–
232, 2005.
[4] M. I. Mandel et al., in Adv. NIPS, pp. 953–960,
2006.
[5] S. Araki et al., Signal Process., 87(8), pp. 1833–
1847, 2007.
[6] ઘଞ, Իߨ (य़), 2-1-5, pp. 555–556ɼ2007ɽ
[7] H. Sawada et al., IEEE Trans. ASLP, 19(3),
pp. 516–527, 2010.
[8] ُԬଞɼԻߨ (य़), 1-1-19, pp. 713–716ɼ2012ɽ
[9] T. Otsuka et al., in Proc. AAAI-12 pp. 2038–
2045, 2012.
[10] A. Kurematsu et al., Speech Communication,
pp. 357–363, 1990.
[11] S. Nakamura et al.,
p. 965–968, 2000.
in Proc. LREC ’00, p-
[12] E. Vincent et al., IEEE Trans. ASLP, pp. 1462–
1469, 2006.
͓ΘΓʹ
ຊߘͰɼԻ͕ݯҠಈ͢Δ͜ͱͰࠞ߹աఔ͕มԽ
͢Δ߹ʹ͓͍ͯ҆ఆͯ͠ಈ࡞͢Δ BSS ΞϧΰϦ
日本音響学会講演論文集
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2013年9月
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