Abstract
Syllable word segmentations as a part of Chinese phonetic input methods (CPIM) involve more overlapping boundaries than word segmentations because of homophone ambiguities. A CPIM usually assumes that the input is a complete sentence, and evaluates the performance based on a well-formed corpus. However, most Pinyin users prefer progressive text entry in short chunks, mainly in one or two words each, which is even more popular on handheld devices with limited computing power. Short chunks do not provide enough contexts to perform the best possible syllable-to-character conversion, especially when a chunk consists of overlapping boundaries. Those overlapping ambiguities show directional tendencies. This dissertation proposes a double ranking (DR) strategy on the left and right context. Experiments show that DR has the benefits of less memory with competitive performance compared to the frequency-based method (low memory and fast) and the conditional random fields model (larger memory and slower).