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In todays Internet world, so many people are using social media services such as Twitter, Facebook, Google+ etc. Automatic summarization of Twitter messages (tweets) is an urgent need for efficient processing of the tweeted information.Twitter topic summarization deals with short, dissimilar, and noisy nature of tweets. In this work, from given twitter tweet under particular trending topic first we recognize speech acts(i.e statement,Suggestion,Question and Comment) in tweets.Depending on majority of speech act we extract key words and phrases from the tweets.Then extracted key words and phrases are ranked and inserted into special summary templates which is designed for speech acts. Finally we generate template based summary. This proposed approach makes a solid contribution to the summarization community.