An Abstractive Approach to Sentence Compression

In this article we generalize the sentence compression task. Rather than simply shorten a sentence by deleting words or constituents, as in previous work, we rewrite it using additional operations such as substitution, reordering, and insertion. We present an experimental study showing that humans can naturally create abstractive sentences using a variety of rewrite operations, not just deletion. We next create a new corpus that is suited to the abstractive compression task and formulate a discriminative tree-to-tree transduction model that can account for structural and lexical mismatches. The model incorporates a grammar extraction method, uses a language model for coherent output, and can be easily tuned to a wide range of compression-specific loss functions.