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
Budzianowski et al. - EMNLP 2018 - MultiWOZ - A...
Search
tosho
December 10, 2018
Research
370
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
Budzianowski et al. - EMNLP 2018 - MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling
tosho
December 10, 2018
More Decks by tosho
See All by tosho
LayerXにおけるセキュリティ管理の現在地と次の一手
tosho
0
530
Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation
tosho
0
340
Good for Misconceived Reasons: An Empirical Revisiting on the Need for Visual Context in Multimodal Machine Translation
tosho
0
400
Shaham and Levy, 2021. Neural Machine Translation without Embeddings. NAACL2021
tosho
0
140
Liu et al., 2021. Pay Attention to MLPs. arXiv
tosho
0
200
Huang et al. 2020 Unsupervised Multimodal Neural Machine Translation with Pseudo Visual Pivoting
tosho
0
500
Ive, Madhyastha, Specia_2019_EMNLP_Deep Copycat Networks for Text-to-Text Generation
tosho
0
180
Tan, Bansal_2019_EMNLP_LXMERT Learning Cross-Modality Encoder Representations from Transformers
tosho
0
280
Tsai et al._2019_ACL_Multimodal Transformer for Unaligned Multimodal Language Sequences
tosho
0
470
Other Decks in Research
See All in Research
nlp2026 In-Context Learningに基づく経路案内のための地理的知識の活用方法に関する検討
takashiinui
0
130
医療LLMの現在地〜最新研究から社会実装までを考える〜
kento1109
1
1.7k
【ローカルAIに向き合う展示会vol.2】液体時間定数型モジュールを用いた オリジナルの双方向エンコーダーモデルNexteraBERT 推論速度向上検討並びにダウンストリーム評価
rikkabotan7
0
180
Fukui Shibiten 39 - AI Art
butchi
0
180
NII S. Koyama's Lab Research Overview AY2026
skoyamalab
0
560
セマンティック通信勉強会 6Gに向けたデバイス間効率的な通信の技術紹介・課題・今後展望
satai
3
290
Research Engineerという仕事 / Research Engineering: Bridging Research and Business
chck
1
280
XDPerf: A High-Performance Traffic Generator Built with WASM and eBPF
takehaya
1
260
Sleuthcon Keynote - How Cybercriminals (ab)use AI
fr0gger
0
300
COMETAを用いたデータ民主化運動の歴史
sazimai
0
230
超効率化への挑戦:1bit LLMの現状と展望
yumaichikawa
0
560
JICA QUEST 共創×革新プログラム Impact Report(海ノ向こうコーヒー)
ontheslope
0
450
Featured
See All Featured
Unsuck your backbone
ammeep
672
58k
SEOcharity - Dark patterns in SEO and UX: How to avoid them and build a more ethical web
sarafernandez
0
250
Save Time (by Creating Custom Rails Generators)
garrettdimon
PRO
32
4.5k
The untapped power of vector embeddings
frankvandijk
2
1.8k
Game over? The fight for quality and originality in the time of robots
wayneb77
1
250
Statistics for Hackers
jakevdp
799
230k
[Rails World 2023 - Day 1 Closing Keynote] - The Magic of Rails
eileencodes
38
3k
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
kevinliebholz
37
6.6k
Everyday Curiosity
cassininazir
0
290
Agile that works and the tools we love
rasmusluckow
331
22k
The agentic SEO stack - context over prompts
schlessera
0
880
Visual Storytelling: How to be a Superhuman Communicator
reverentgeek
2
630
Transcript
MultiWOZ – A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue
Modeling Tosho Hirasawa
0. Overview • -6<+?E$> • 4L3I/%) H2 • :@Multi-Domain
Wizard-of-Oz (MultiWOZ) • KJ • ("*72 GA/9F8 #!= 5 ,1 • 0.BD&* ' &(*;C
1. Introduction • Conversational Artificial Intelligence • human-level *)&($ •
#%' ! • Seneff and Polifroni, 2000 • "Raux et al., 2005 • Amazon AlexaRam et al., 2018
1. Introduction • \T@F [C0*%0# RA •
2DKU • =W:J • ?6) 8V • OXN3A • PH517 E2E ,"/LI • <];Z17MYB( >E • &!-0Q • " 9 • [C$+0_4D • GS5'.-0^
1. Introduction , , 2017
2. Related Works • >K&.(%3/9 ! • Machine-to-Machine • *5/4+"O6K"R
• HLJ-$) T DM6K\E ]X • Human-to-Machine • 7:=@^Y'(*0UZ9";I • G OE! :B • HLJ^Y'(*0 YS?,1$5&.(NI • Human-to-Human • G<QW &(+< • Twitter, Reddit, Ubuntu 6K"_8NI! • HLJ6KC[ AP#-*'25 FV
3. Data Collection Set-up • Wizard-of-Oz E4 • Dialogue Task:
• *,-@ ontology random sampling !'#%"8(6 • User Side: • (6=1 97CF.;A • System (Wizard) Side: • $ 2: 97/D • Wizard/User (6>, (6JG+ • (6)I30< • (6H5&?B)I30
3. Data Collection Set-up • Annotation of Dialogue Acts •
Dialogue Act = intent + slot-value pairs • intent: inform / request • slot-value: domain, price, … • Amazon Mechanical Turk +!" &$ dialogue acts .) • !" &$ '- /( • % ,*0.8843#0
4. MultiWOZ Dialogue Corpus •
: domain
4. MultiWOZ Dialogue Corpus : expensive : domain
4. MultiWOZ Dialogue Corpus • (turns in a
dialogue) • 8.93 (single-domain), 15.39 (multi-domain) • 115,434 turns • >70% 10 turns • (sentence length) • 11.75 (user), 15.12 (wizard)
4. MultiWOZ Dialogue Corpus • Dialogue Acts • 60% turns
action • %# • "$ • %# !"$
4. MultiWOZ Dialogue Corpus • •
• Multi-Domain, Dialogue Act
5. MultiWOZ as a New Benchmark • Dialogue modelling task
• Dialogue State Tracking • (,# '/ • &,.5-0)1 ontology • Dialogue-Context-to-Text Generation • (,Dialogue State, # '/ • &,!16 • Cam676/MultiWOZ 28 • % $"+* • RNN 473 • Cam676: GRU • MultiWOZ: LSTM
5. MultiWOZ as a New Benchmark • Dialogue-Act-to-Text Generation •
Structured meaning representation (Dialogue Act?) • • Semantically Conditioned LSTM (Wen+, 2015) • SFX MultiWOZ restaurant • SER = (missing slots + redundant slots) / total slots Wen+, 2015
6. Conclusion • )1"&7* 8 E2E #$20
• Modular-based (+%' • MultiWOZ 3 46 • !-53. github /,