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3 months ago

Speaker-Aware Discourse Parsing on Multi-Party Dialogues

{Min Zhang Guohong Fu Nan Yu}

Speaker-Aware Discourse Parsing on Multi-Party Dialogues

Abstract

Discourse parsing on multi-party dialogues is an important but difficult task in dialogue systems and conversational analysis. It is believed that speaker interactions are helpful for this task. However, most previous research ignores speaker interactions between different speakers. To this end, we present a speaker-aware model for this task. Concretely, we propose a speaker-context interaction joint encoding (SCIJE) approach, using the interaction features between different speakers. In addition, we propose a second-stage pre-training task, same speaker prediction (SSP), enhancing the conversational context representations by predicting whether two utterances are from the same speaker. Experiments on two standard benchmark datasets show that the proposed model achieves the best-reported performance in the literature. We will release the codes of this paper to facilitate future research.

Benchmarks

BenchmarkMethodologyMetrics
discourse-parsing-on-molweniSSP-BERT + SCIJE
Link u0026 Rel F1: 59.4
Link F1: 83.7
discourse-parsing-on-stacSSP-BERT + SCIJE
Link u0026 Rel F1: 57.4
Link F1: 73.0

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Speaker-Aware Discourse Parsing on Multi-Party Dialogues | Papers | HyperAI