For example, " Ä" could be treated as a single word (Bank of Beijing) for machine translation, while it is more naturally segmented into " (Beijing) Ä (bank)" for tasks such as text-to-speech synthesis.
several discriminatively trained models have recently been applied to the CWs problem.