Tree-Structured Neural Machine for Linguistics-Aware Sentence Generation

Understand

Different from other sequential data, sentences in natural language are structured by linguistic grammars.

• Previous generative conversational models with chain-structured decoder ignore this structure in human language and might generate plausible responses with less satisfactory relevance and fluency.
• In this study, we aim to incorporate the results from linguistic analysis into the process of sentence generation for high-quality conversation generation.
• Specifically, we use a dependency parser to transform each response sentence into a dependency tree and construct a training corpus of sentence-tree pairs.