An architecture for Malay Tweet normalization
To observe features of Malay Tweets, three distinct corpus-based analyses are done. A rule-based architecture is developed based on results of the analyses. The architecture consists of seven distinct modules in a pipeline structure. Experimental results indicate high accuracy in term of BLEU score. The architecture outperforms SMT-like normalization approach.
malay twitter text normalization noisy text