Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Sign up for free
Menu
Search
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Pricing
Search
Sign in
Sign up for free
Fundamentals of Music Processing (Chapter 5)
Search
Koga Kobayashi
December 12, 2019
Research
110
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
Fundamentals of Music Processing (Chapter 5)
Koga Kobayashi
December 12, 2019
More Decks by Koga Kobayashi
See All by Koga Kobayashi
第13回 Data-Centric AI勉強会, LLMのファインチューニングデータ
kajyuuen
4
1.9k
基礎数学の公式
kajyuuen
1
190
初等確率論の基礎
kajyuuen
1
210
Deep Markov Model を数式で追う (+ Pyroでの追試)
kajyuuen
0
960
完全なアノテーションが得られない状況下での固有表現抽出
kajyuuen
3
3.7k
SecHack365 北海道会 LT
kajyuuen
0
550
専門用語抽出手法の研究と 抽出アプリケーションの開発
kajyuuen
1
1.3k
Other Decks in Research
See All in Research
Apache Gravitinoで実現する Icebergカタログ統合とアクセスの一元化
matsumooon
0
510
Source Code Diff Revolution
tsantalis
0
150
第64回CV・PRML勉強会 論文紹介:Linguistic Priors for Visual Decoupling: Towards Symmetric Vision-Brain Alignment
sokikatayama
0
200
最先端NLP勉強会2026 論文紹介:Reasoning with Sampling: Your Base Model is Smarter Than You Think (ICLR 2026 paper)
kogoro
4
610
[SNLP2026] Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
wataruuuuu
0
310
研究室単位での自律的 IPv6接続性確立に向けたAS共同運用モデルの提案と実証
reokashiwa
PRO
0
210
Fukui Shibiten 39 - AI Art
butchi
0
190
全国町字単位空き家率推定データver1.0データ仕様
microbaseinc
0
240
実例から見るLLMのマンガ理解:実務VQAタスクによる長期的文脈と視覚情報の定性評価
kzmssk
0
130
論文紹介:Doc-to-LoRA: Learning to Instantly Internalize Contexts
yukako_nakano
0
160
クラウド・AI 時代の研究開発 DX / R&D Digital Transformation
hariby
0
140
COMETAを用いたデータ民主化運動の歴史
sazimai
0
250
Featured
See All Featured
Test your architecture with Archunit
thirion
2
2.4k
Testing 201, or: Great Expectations
jmmastey
46
8.3k
Design in an AI World
tapps
1
310
The browser strikes back
jonoalderson
0
1.7k
Easily Structure & Communicate Ideas using Wireframe
afnizarnur
194
17k
"I'm Feeling Lucky" - Building Great Search Experiences for Today's Users (#IAC19)
danielanewman
230
23k
SEOcharity - Dark patterns in SEO and UX: How to avoid them and build a more ethical web
sarafernandez
0
280
Un-Boring Meetings
codingconduct
0
420
We Analyzed 250 Million AI Search Results: Here's What I Found
joshbly
1
1.9k
Raft: Consensus for Rubyists
vanstee
141
7.7k
Paper Plane
katiecoart
PRO
3
53k
No one is an island. Learnings from fostering a developers community.
thoeni
21
3.8k
Transcript
Fundamentals of Music Processing Chapter 5: Chord Recognition খྛ
ᕣՏ εϥΠυʹؚ·ΕΔਤFundamentals of Music ProcessingΑΓҾ༻
Chapter 5: Chord Recognition Chord(Ի) • 3ͭҎ্ͷҟͳΔԻූ͔Βߏ͞ΕΔԻͷ͜ͱ Harmony() • ෳͷԻ͔ΒͳΔܥྻɺԻਐߦ
FM7 G7 Em7 Am Harmony
Chapter 5: Chord Recognition Chord Recognition(Իೝࣝ) • Ի͔ΒԻਐߦΛೝࣝ͢Δٕज़ ԻָϑΝΠϧ͔ΒίʔυේΛࣗಈͰ࡞ग़དྷΔ Իೝ͕ࣝ͏·͍͘͘ͱ…
Chapter 5.3: HMM-Based Chord Recognition Chapter 5.1~5.2 • ಛྔ͔ΒԻΛ͋Δఔਪఆग़དྷΔ ͔͠͠ɺ͜ΕԻҰͭҰ͔ͭ͠ݟ͍ͯͳ͍
Α͘ग़ΔԻܨ͕Γͷڧ͍Իʹண͍ͨ͠ ྫ: I–IV–V–Iਐߦ • FGසग़͠ɺ͍͖ͳΓFmʹߦ͘͜ͱ΄΅ແ͍ HMM(ӅΕϚϧίϑϞσϧ)Λར༻ͯ͠ԻਪఆΛߦ͏
Chapter 5.3: HMM-Based Chord Recognition Ի: , ঢ়ଶ: (for )
ͱͨ͠ͱ͖ɺϚϧίϑੑΛԾఆ͢Δͱ Ͱ͋Δ֬ A := {α1 , α2 , ⋯, αI } s i ∈ [1 : I] sn+1 = αj P[sn+1 = αj |sn = αi , sn−1 = αk , ⋯] = P[sn+1 = αj |P[sn+1 = αj |sn ] ͜͜Ͱ ΛҎԼͷΑ͏ʹఆٛ͢Δɻ(for ) aij i, j ∈ [1 : I] ͜Εঢ়ଶ͕ ͔Β ʹભҠ͢Δ֬ͱߟ͑Δ͜ͱ͕ग़དྷΔ αi αj aij := P[sn+1 = αj |sn = αi ] ∈ [0,1] ·ͣɺϚϧίϑ࿈Λར༻ͨ͠Ի༧ଌʹ͍ͭͯઆ໌͢Δ
Chapter 5.3: HMM-Based Chord Recognition ۩ମྫ; , ͷͱ͖ I =
3 A := {α1 = C, α2 = G, α3 = F} ·ͨ࠷ॳͷঢ়ଶ͕ Ͱ͋Δ֬ΛҎԼͷΑ͏ʹఆٛ͢Δ αi ci := P[s1 = αi ] ∈ [0,1]
Chapter 5.3: HMM-Based Chord Recognition , , ͷͱ͖ ঢ়ଶܥྻ: ʹ͍ͭͯߟ͑Δ
I = 3 A := {α1 = C, α2 = G, α3 = F} C = (c1 , c2 , c3 )T = (0.6,0.2,0.3)T S = (C, C, C, G, G, F, F, C, C) ࠷ॳͷঢ়ଶ͕ Ͱ͋Δ֬ΛҎԼͷΑ͏ʹఆٛ͠ɺ αi ci := P[s1 = αi ] ∈ [0,1] ۩ମྫ
Chapter 5.3: HMM-Based Chord Recognition ભҠ͕֬ҎԼͷͱ͖ ͷΑ͏ͳԻਐߦ͕ى͖Δ֬ S S =
(C, C, C, G, G, F, F, C, C) = c1 ⋅ a11 ⋅ a11 ⋅ a12 ⋅ a22 ⋅ a23 ⋅ a33 ⋅ a31 ⋅ a11 ≈ 1.29 ⋅ 10−4
Chapter 5.3: HMM-Based Chord Recognition ઌఔঢ়ଶܥྻ Λ༻͍ͯɺԻਐߦͷ֬Λܭࢉ͕ͨ͠ ࣮ੈքͰऔΓ͏Δͯ͢ͷ ʹ͍ͭͯܭࢉෆՄೳ S
S ྫ: 10छྨͷԻɺ20͔ͭΒߏ͞ΕΔۂͷ߹ ύλʔϯͷ֬Λܭࢉ͢Δඞཁ͕͋Δ 1020 ͦ͜Ͱ෦ͷঢ়ଶͰͳ͘ɺಛϕΫτϧΛ༻͍ͯ ԻਐߦΛٻΊΔํ๏ͱͯ͠HMMΛར༻͢Δɻ
Chapter 5.3: HMM-Based Chord Recognition
Chapter 5.3: HMM-Based Chord Recognition
Chapter 5.3: HMM-Based Chord Recognition Input: Իσʔλ͔Β؍ଌͨ͠ܥྻ ͔Β ϞσϧΛར༻͠ɺ؍ଌܥྻ Λ࡞ɻ
O = (o1 , ⋯, oN ) B = (β1 , ⋯, βN ) ؍ଌܥྻ ؍ଌγϯϘϧ ͔Βߏ͞ΕΔ B = (β1 , ⋯, βN ) ℬ = {β1 , ⋯, βk } (for k ∈ [1 : K])
Chapter 5.3: HMM-Based Chord Recognition
Chapter 5.3: HMM-Based Chord Recognition Viterbi: ؍ଌܥྻ ͱ ॳظঢ়ଶͷ֬
ੜ֬ͱભҠ͔֬Β༗άϥϑΛ࡞ B = (β1 , ⋯, βN ) C = (c1 , c2 , c3 )T = (0.6,0.2,0.3)T ੜ֬ ભҠ֬
Chapter 5.3: HMM-Based Chord Recognition ੜ֬ ભҠ֬ ॳظঢ়ଶͷ֬ ੜ͞Εͨ༗άϥϑ
Chapter 5.3: HMM-Based Chord Recognition ViterbiΞϧΰϦζϜʹΑͬͯ ࠷Β͍͠ܦ࿏ʹ͍ͭͯܭࢉΛߦ͏
Chapter 5.3: HMM-Based Chord Recognition ੜ͞Εͨ༗άϥϑ ViterbiΞϧΰϦζϜͰ֤ҐஔͰɺ ֤ԻʹͨͲΓண͘·Ͱͷ࠷దίετͱ ͦͷલʹࢸΔ·ͰͷϙΠϯλΛ֮͑ͳ͕ΒܭࢉΛߦ͏
Chapter 5.3: HMM-Based Chord Recognition ੜ͞Εͨ༗άϥϑ ViterbiΞϧΰϦζϜͰ֤ҐஔͰɺ ֤ԻʹͨͲΓண͘·Ͱͷ࠷దίετͱ ͦͷલʹࢸΔ·ͰͷϙΠϯλΛ֮͑ͳ͕ΒܭࢉΛߦ͏
Chapter 5.3: HMM-Based Chord Recognition ੜ͞Εͨ༗άϥϑ ViterbiΞϧΰϦζϜͰ֤ҐஔͰɺ ֤ԻʹͨͲΓண͘·Ͱͷ࠷దίετͱ ͦͷલʹࢸΔ·ͰͷϙΠϯλΛ֮͑ͳ͕ΒܭࢉΛߦ͏
Chapter 5.3: HMM-Based Chord Recognition ੜ͞Εͨ༗άϥϑ ViterbiΞϧΰϦζϜͰ֤ҐஔͰɺ ֤ԻʹͨͲΓண͘·Ͱͷ࠷దίετͱ ͦͷલʹࢸΔ·ͰͷϙΠϯλΛ֮͑ͳ͕ΒܭࢉΛߦ͏
Chapter 5.3: HMM-Based Chord Recognition ੜ͞Εͨ༗άϥϑ ViterbiΞϧΰϦζϜͰ֤ҐஔͰɺ ֤ԻʹͨͲΓண͘·Ͱͷ࠷దίετͱ ͦͷલʹࢸΔ·ͰͷϙΠϯλΛ֮͑ͳ͕ΒܭࢉΛߦ͏
Chapter 5.3: HMM-Based Chord Recognition ੜ͞Εͨ༗άϥϑ ViterbiΞϧΰϦζϜͰ֤ҐஔͰɺ ֤ԻʹͨͲΓண͘·Ͱͷ࠷దίετͱ ͦͷલʹࢸΔ·ͰͷϙΠϯλΛ֮͑ͳ͕ΒܭࢉΛߦ͏
Chapter 5.3: HMM-Based Chord Recognition ࠷ޙʹɺͦͷϙΠϯλΛḷΓ࠷Β͍͠ԻਐߦΛ ٻΊΔ A := {α1
= C, α2 = G, α3 = F} ͷͱ͖ ̂ S = (C, C, C, G, G, F)