Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Exercises for Patterns in Recordings
Search
Ben Fields
July 05, 2016
Technology
0
44
Exercises for Patterns in Recordings
from DHOxSS 2015-16
Ben Fields
July 05, 2016
Tweet
Share
More Decks by Ben Fields
See All by Ben Fields
People in the loop machine learning: A case Study in news similarity
bfields
0
150
Human-centric evaluation of similarity spaces of news articles
bfields
2
63
Ethics, Data Science, and Public Service Media
bfields
1
60
The Case for Public Service Recommender Algorithms
bfields
0
720
Bikes are Dope
bfields
0
72
Beyond Your Reckons: from feels to facts
bfields
0
83
People who like cheese also like crackers: a learning hour on recommender systems
bfields
0
90
Auto-Summarising Beer Reviews
bfields
0
75
rMIXr: how we learned to stop worrying and love the graph
bfields
0
110
Other Decks in Technology
See All in Technology
AIのグローバルトレンド 2025 / ai global trend 2025
kyonmm
PRO
1
120
2時間で300+テーブルをデータ基盤に連携するためのAI活用 / FukuokaDataEngineer
sansan_randd
0
130
【2025 Japan AWS Jr. Champions Ignition】点から線、線から面へ〜僕たちが起こすコラボレーション・ムーブメント〜
amixedcolor
1
120
Perlアプリケーションで トレースを実装するまでの 工夫と苦労話
masayoshi
1
410
JAWS AI/ML #30 AI コーディング IDE "Kiro" を触ってみよう
inariku
3
270
Google Agentspaceを実際に導入した効果と今後の展望
mixi_engineers
PRO
2
330
ビジネス文書に特化した基盤モデル開発 / SaaSxML_Session_2
sansan_randd
0
260
猫でもわかるQ_CLI(CDK開発編)+ちょっとだけKiro
kentapapa
0
3.4k
AIエージェントを現場で使う / 2025.08.07 著者陣に聞く!現場で活用するためのAIエージェント実践入門(Findyランチセッション)
smiyawaki0820
6
550
Amazon Q Developerを活用したアーキテクチャのリファクタリング
k1nakayama
2
180
僕たちが「開発しやすさ」を求め 模索し続けたアーキテクチャ #アーキテクチャ勉強会_findy
bengo4com
0
1.9k
【CEDEC2025】大規模言語モデルを活用したゲーム内会話パートのスクリプト作成支援への取り組み
cygames
PRO
2
770
Featured
See All Featured
The Illustrated Children's Guide to Kubernetes
chrisshort
48
50k
How to train your dragon (web standard)
notwaldorf
96
6.1k
Save Time (by Creating Custom Rails Generators)
garrettdimon
PRO
31
1.3k
Making Projects Easy
brettharned
117
6.3k
Agile that works and the tools we love
rasmusluckow
329
21k
Automating Front-end Workflow
addyosmani
1370
200k
Rebuilding a faster, lazier Slack
samanthasiow
83
9.1k
XXLCSS - How to scale CSS and keep your sanity
sugarenia
248
1.3M
Fantastic passwords and where to find them - at NoRuKo
philnash
51
3.4k
Building an army of robots
kneath
306
45k
How GitHub (no longer) Works
holman
314
140k
[Rails World 2023 - Day 1 Closing Keynote] - The Magic of Rails
eileencodes
35
2.5k
Transcript
Patterns in Recording - Exercises Ben Fields
WEKA basics • Launch the WEKA Application • Select ‘Explorer’
• Load ’50_weka_class_labeled.arff’ • Select various Attributes (features)
WEKA basics • Attribute selection with regular expressions (‘.*’ is
an expanding wild card) • Find all the MFCC attributes • also select ‘CLASS’ • press ‘Invert’, then ‘Remove’
using a classifier • Select ‘Classify’ tab • ‘Choose’ >>
‘classifiers/bayes/ NaiveBayes’ • set test options to ‘Cross-validation’ • press ‘Start’
putting it all together • now repeat the whole process
using LPC features
Explore more files and features • Load ‘training_data_after_parsing.arff’ • Classify
against the CLASS mood labels using Random Forests and J48. Which performs better? Which classes are most confused?