Non-Standard Word Labeling

NSW(Non-Standard Word): Digits(123 pages, stock id: 2412, 3/2, 2/3, Phone number, date-time, range, currency), Internet Symbols(:-)), %, Abbreviations, URLs, Poyins

NSW Labeling are an important task in Chinese Text-to-Speech

Goal: How to Label NSW Correctly and translate a NSW into a Oral Expression ?
=>Try to train a corpus-based statistical model and to observe patterns from data carefully in order to define some rules.

Homograph Disambiguation

Goal: To Find the Best-fit Pronunciation from the Multiple Pronunciations of a Term
=> e.g., “沈外科”(ㄕㄣˇ), “沈下去”(ㄔㄣˊ)

POS(part-of-speech)-tagging v.s. Statistics(Term-Term Relation)

Calculate the Probability of Targeted Terms with Multiple Pronunciations

Disambiguate those Terms in Lexicons using Word-Sense Disambiguation(a problem of the WSD: 全台大搜索)

Calculate Term-Term Relation to Find out one of the Best Possible Pronunciations

A Corpus-based Transliteration Model for English-Chinese Named Entity Translation

Goal: To Find out a Best-fit Transliteration for a Foreign Personal Name(*), a Foreign Organization Name
=>General “Powell”(The Secretary of the State, US): “包爾” or “包威爾”

Forward Translation: E->C, Backward Translation:C->E

The Corpus Source: Using Anchored-text Analysis and Extracting Pairs of Terms from the Web

Translation by Semantics or Pronunciations(*)

The Pronunciation Dictionary Source: The CMU Pronunciation Dictionary Project.

2003-01-15T13:19:35