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Kotonoha: An Example Sentence Based Spaced Repetition System
- 1. Kotonoha An Example Sentence Based Spaced Repetition System Arseny Tolmachev, Sadao Kurohashi Kyoto University Graduate School of Informatics D1 2017-03-15
- 2. Background: Learning words with flashcards • Lexical knowledge is crucial for language learning • Mostly self-learning • E.g. Japanese Language Proficiency Test level N1 requires knowing about 10,000 words 2 Flashcards: a method of organizing information, which can be formulated in question-answer form, for learning Question Answer
- 3. Spaced Repetition 3graph is from supermemo.com website
- 4. Spaced Repetition: Software • One of first implementations: https://www.supermemo.com • The most popular SRS: Anki http://ankisrs.net/ • And much more 4
- 5. Japanese (Word) Learning Tools • Most of them are for elementary/beginner learners • Hiragana/katakana • Fixed word lists/lessons • Tools for advanced learners are scarce • Anki • Several more 5
- 6. Motivation: Context • We use words in context: with other words • Contextual word usage differ from language to language Life example: • バスは乗客を拾った Non-canonical usage in Japanese, OK in Russian • バスは乗客を乗せた Canonical usage in Japanese 6
- 7. Flashcard problems • Creating flashcards from scratch is time-consuming • Need to fill all information • Possibly find example sentences somewhere • Premade decks do not work as well as manually created • Matter of UI and system implementation • Lack of context • Especially in questions • Card content is usually fixed (e.g. only one context) 7
- 8. Kotonoha SRS • Web (responsive) • +mobile apps (in plans) • Flashcards • Spaced Repetition • Intermediate+ Features • Example sentences • In question cards • Batch operation • Japanese-oriented 8 https://kotonoha.ws
- 9. Kotonoha: Usage Pattern • Find new words • Reading books, classes, assignments • Add words into the system • Kotonoha makes it easy to add new words • Repeat flashcards • E.g 100 cards every day • Learn word usage too: Kotonoha shows a new example each repetition • Have a rich vocabulary (in a long term) 9
- 10. Kotonoha: Adding words 10 Batch operation Words are added in lists Kotonoha fills reading and glosses from dictionary (JMDict, Warodai) Kotonoha assigns example sentences Easy to learn words you want Word was already added Word was not added before Report that you forgot the word
- 11. Kotonoha: Adding words (2) 11 Check what gets into flashcards Recommendations: words using same characters
- 12. Kotonoha: Repetition 12 Question card (reading) Answer card
- 13. Kotonoha: Writing Printouts 13 Print out and practice writing difficult words
- 14. Example sentences • Automatically extracted from web corpus • Tatoeba corpus is small and not very diverse • Consider a set of sentences for a target word • Three aspects: Value, Diversity, Coverage • Intrinsic Value (for a single sentence) • Not a garbage sentence like a fragment of something • Representative usage of target • Understandable by a learner • Grammatical • Diversity (for a sentence set) • Different usages of target, distinct words • Coverage: acquire usages of rare words and rare senses 14
- 15. Example sentence extraction overview 15 私は走るのすき 走っている子供を見た … 遊びに走る若者 酒に走りたい気持ち … 悪事千里を走る Query 走る Search Engine High-quality sentences (~10-15) Preprocessing Raw Corpus Analyze and index Search Selection Solving coverage problem Dealing with value and diversity • Distributed • Handles huge corpora • Uses lexical dependency information • Prefers sentences with rich syntactic structure near target Example Candidates (~10k sentences) Details are out of scope of this presentation
- 20. Example sentence evaluation This is idea, no results yet Show different sentences to learners of similar level Assumption: Good example sentences help to remember words. Assumption 2: We can use confidence to judge sentence educational quality
- 21. Collecting NLP training data 21 Kotonoha can be useful source of NLP training data for: Reading estimation Word sense disambiguation Learners are interested to get this information right Presently only reporting is implemented
- 22. Implementation problems • Three segmentation standards in one package • Flashcards are mostly JMDict-based • And words over there are rather inconsistent • On the other hand, it is not a segmentation dictionary • Example sentence extraction uses JUMAN/KNP pipeline • Reading estimation is done using KyTea/UniDic • And resources for reading-annotated Japanese are extremely sparse :( • Because of this • Some example sentence coverage problems • Reading estimation errors 22
- 23. Kotonoha: Present • Available: https://kotonoha.ws • Open source (core SRS) • https://github.com/kotonoha/server • (Very low volume) open beta test • Will try to increase user base in following months • Potential users (Japanese Learners) are very welcome! • Side note: • https://github.com/kotonoha/akane • JUMAN/KNP/KyTea + other Scala library 23