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Automatic speech act identification in business emails

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This talk presents an approach to automated speech act recognition in business English emails. A maximum entropy classifier is trained on a combination of lexical and syntactic features, achieving 79% accuracy on non-native English data. I also discuss how varying conditions such as feature selection and training data affect performance.

This talk is part of the NLIP Seminar Series series.

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