ByteCool Software
Sun, 03 May 2009 15:39:22 -0700
A better formatted version is at http://sites.google.com/site/yaoziyuan/ideas Foreign Language Learning Automatic Code-Switching (ACS) - The computer automatically selects a few words in a user's native language communication (such as a web page being viewed), and supplements or even replaces them with their foreign language counterparts, thus naturally building up his vocabulary. For example, if a sentence "他是一个好学生。" (Chinese for "He is a good student.") appears in a Chinese person's Web browser, the computer can insert student after 学生 (optionally with additional information such as student's pronunciation in IPA): 他是一个好学生 (student)。After several times of such teaching, the computer can directly replace future occurrences of 学生 with student. Ambiguous words such as the 看 (Chinese for "see", "look", "watch", "read", etc.) in 他在电视前看书 (Chinese for "He is reading a book before the TV.") can also be automatically handled by listing all context-possible translations: 他在电视前看 (阅读: read; 观看: watch) 书。Practice is also possible: 他在电视前 [read; watch] 书。Because the computer would only teach and/or practice foreign language elements at a small number of positions in the native language article the user is viewing, the user wouldn't find it too intrusive. Automatic code-switching can also teach grammatical knowledge in similar ways. Progressive Word Acquisition (PWA) - In ACS, long words are optionally split into small segments (usually two syllables long) and taught progressively, and even practiced progressively. For example, when 科罗拉多州 (Chinese for "Colorado") first appears in a Chinese person's Web browser, the computer inserts Colo' after it (optionally with Colo's pronunciation): 科罗拉多州 (Colo'); when 科罗拉多州 appears for the second time, the computer may decide to test the user's memory about Colo' so it replaces 科罗拉多州 with Colo' (US state). Note that a hint such as "US state" is necessary in order to differentiate this Colo' from other words beginning with Colo. For the third occurrence of 科罗拉多州, the computer teaches the full form, Colorado, by inserting it after the Chinese occurrence: 科罗拉多州 (Colorado); at the fourth time, the computer may totally replace 科罗拉多州 with Colorado. Not only the foreign language element (Colorado) can emerge gradually, the original native language element (科罗拉多州) can also gradually fade out, either visually or semantically (e.g. 科罗拉多州 -> 美国某州 -! > 地名 -> ∅). This prevents the learner from suddenly losing the Chinese clue, while also engages him in active recalls of the occurrence's complete meaning (科罗拉多州) with gradually reduced clues. Subword Familiarization (SWF) - In ACS, word roots (e.g. pro-, scrib-) and meaningless word fragments (e.g. -ot) are optionally treated as two special kinds of standalone words and taught and practiced in the user's incoming native language information. Meaningless fragments are considered abbreviations and acronyms of real, meaningful words. Getting the learner familiar with all these subword units can facilitate the acquisition of longer, real words that contain them. Phonetics-Enhanced English (PEE) - The computer can add non-intrusive diacritical marks (e.g. the mark in á) above normal English words to better reflect their pronunciations. Unlike radical spelling reform proposals, a word's original literal form is always preserved. Unlike annotating words with their IPA forms above, diacritical marks are closely integrated with letters so a learner can "read once and learn both the literal and the phonetic form." In inputting English, the learner still uses the original literal form only. Computer-Assisted Foreign Language Writing Input-Driven Syntax Aid (IDSA) - As a non-native English user inputs a word, e.g. search, the word's sentence-making syntaxes are prompted by the computer, e.g. v. search: n. searcher search~ [n. search scope] [for n. search target] so he can now write a syntactically valid sentence like "I'm searching the room for the cat." Input-Driven Ontology Aid (IDOA) - As a non-native English user inputs a word, e.g. badminton, things and relations that normally co-exist with the word in the same scenario or domain are prompted as a systematic ontology graph by the computer, e.g. entities like racquet, shuttlecock and playing court, relations like alternate, serve and strike, and even full-scripted composition templates like template: a badminton game. The benefits of the ontology aid are twofold. First, the ontology helps the user verify that the "seed word", badminton, is a valid concept in the intended scenario (or context); second, the ontology pre-emptively exposes other valid words in this context to the user, preventing him from using a wrong word, e.g. bat (instead of racquet), from the very beginning. Foreign Language Reading without Learning that Language Full-Automatic Layered-Quality Machine Translation (FALQ-MT) - Lexical and syntactic ambiguities are translated to fuzzy concepts and structures instead of precise but error-prone results. Less information is better than misinformation. If the reader can't guess the meaning of a fuzzy occurrence from its context, he can "zoom in" and see more detailed translation possibilities if he feels that occurrence is important. Natural Disambiguation (NATDISAMB) - A native reader perceives a multi-sense word not by enumerating all possible senses of that word one by one in his mind and validating each one against the context. Instead, the word is a multi-faceted body in his mind, each facet orienting to one domain and displaying a sense corresponding to that domain, and the context is a driving force that positions the mind's eye into an anticipated domain and from there the mind's eye sees only one facet of the body. Other facets (senses) are mentally inhibited right from the beginning. This process can be simulated for a person who doesn't know a language at all to "act like" the native reader: The computer translates the source language document to the person's native language, presenting unresolved ambiguous words as multi-row objects, each row corresponding to a formerly defined domain and displaying a sense corresponding to that domain. The reader, previously instructed which row corresponds to what domain, doesn't have to read every row of such a multi-row object and find the sense that fits the context, but just needs to predict, based on previous context, which domain the upcoming word will come from, and accordingly look at the corresponding row, and voila! He got the right sense. Foreign Language Writing without Learning that Language Formal Language Writing and Machine Translation (FLW) - A person not knowing a target language can generate information in that language by composing in a formal language based on his native language and having the composition machine-translated. Tools such as the input-driven syntax aid and input-driven ontology aid can be borrowed to assist the person in formal language writing. The idea of natural disambiguation can also be adapted here, so that the author can intuitively specify an intended sense for a word he has just entered, without going through all candidates. Ontology-Based Resource Sharing Wikipedia-Based Resource Sharing (WP-RES) - A useful property of Wikipedia is that each Wikipedia article or category can serve as a unique address, or "coordinates", for the topic it corresponds to. With this property, we can enable people with the same interest to rendezvous at the same Wikipedia page and therefore talk with each other. People could also register resources at a Wikipedia page's External Links section so that other people with the same interest can find them. People could even "subscribe" to a Wikipedia page for new and updated resources and opportunities on that topic.Ontology-Based Problem-Solving Skills Sharing Wikipedia: From Knowledgebase to Strategybase (STRABASE) - If we're solving a problem, say, a math problem, we choose a seemingly promising strategy from our "strategy bases" in our minds, according to the problem's main type and characteristic conditions. Such a "strategy base" is something we can build up externally using a wiki. A "strategy" is a special kind of knowledge that caters to certain problem characteristics and provides certain problem-solving frameworks. The wiki can store and categorize strategies and domain knowledge by their intended problem types and characteristics, so the human can better evaluate, select and apply strategies relevant to his problem.Miscellaneous Chinese Pinyin Input Method Revisited (PYIME) - Today's Chinese pinyin input methods inherit the single-row candidates window from the DOS era. If we categorize candidate characters into multiple rows according to some criteria, the user can more easily home in on his desired character. For example, each row contains characters that have the same phonetic radical, and one row reads "马 吗 妈 码 玛", while another row reads "麻 嘛 䗫". Rows can also correspond to the five possible tones in Chinese. Still, there can be a special, first row for the most frequently used words and characters. A Politically Correct New Name for English (ARCS) - As technology like automatic code-switching would make English a much cheaper commodity for non-native people to acquire, for the first time it will become possible for most people in the world to use decent English. But nationalist sentiments can be a negative factor for some people to adopt English. While it is logically recognized by everybody that all natural languages are actually made of equally random syllables, emotionally people can still more or less feel unequal that one language is more international than others. A reason for this paradox is that languages are named by their nations of origin: English, French, Spanish, etc. Therefore, we can use a "renaming" technique to better reflect a language's random nature rather than nationalist connotation. Actually, the word "language" itself already has a strong nationalist connotation, and I propose the term "code system" to eliminate that connotation. As for English, let's rename it as "A Random Code System", or ARCS for short. _________________________________________________________________ Hotmail® has a new way to see what's up with your friends. http://windowslive.com/Tutorial/Hotmail/WhatsNew?ocid=TXT_TAGLM_WL_HM_Tutorial_WhatsNew1_052009 _______________________________________________ Mt-list mailing list