Learning Chinese-specific encoding for phonetic similarity

Learning Chinese-specific encoding for phonetic similarity

5 years ago
Anonymous $L9wC17otzH

https://phys.org/news/2018-11-chinese-specific-encoding-phonetic-similarity.html

Most algorithms for phonetic similarity are motivated by English use cases, and designed for Indo-European languages. However, many languages, such as Chinese, have a different phonetic structure. The speech sound of a Chinese character is represented by a single syllable in Pinyin, the official Romanization system of Chinese. A Pinyin syllable consists of: an (optional) initial (such as 'b', 'zh', or 'x'), a final (such as 'a', 'ou', 'wai', or 'yuan') and tone (of which there are five). Mapping these speech sounds to English phonemes results in a fairly inaccurate representation, and using Indo-European phonetic similarity algorithms further compounds the problem. For example, two well-known algorithms, Soundex and Double Metaphone, index consonants while ignoring vowels (and have no concept of tones).

As a Pinyin syllable represents an average of seven different Chinese characters, the preponderance of homophones is even greater than in English. Meanwhile, the use of Pinyin for text creation is extremely prevalent in mobile and chat applications, both when using speech-to-text and when typing directly, as it is more practical to input a Pinyin syllable and select the intended character. As a result, phonetic-based input mistakes are extremely common, highlighting the need for a very accurate phonetic similarity algorithm that can be relied on to remedy errors.