The Cross-lingual Conversation Summarization Challenge (2022)

Abstract: We propose the shared task of cross-lingual conversation summarization, ConvSumX Challenge, opening new avenues for researchers to investigate solutions that integrate conversation summarization and machine translation. This task can be particularly useful due to the emergence of online meetings and conferences. We use a new benchmark, covering 2 real-world scenarios and 3 language directions, including a low-resource language, for evaluation. We hope that ConvSumX can motivate research to go beyond English and break the barrier for non-English speakers to benefit from recent advances of conversation summarization.

## motivation thanks to the availability of large-scale corpora @xcite @xcite , research on conversation summarization has made great progress @xcite @xcite . however, existing corpora in this area focus on english while ignoring other languages @xcite . such englishdominated corpora lead to a barrier for non-english speakers to benefit from conversation summarization research, which becomes more severe in the era of epidemic, where international meetings are held online and participants communicate in english. convsumx integrates conversation summarization and machine translation, involving the language shift from one to another and stylistic shift from long spoken conversations to concise written monologues. ideally, using the first translate, then summarize and vice versa pipelines can solve the task. however, besides the difficulties in monolingual conversation summarization @xcite , pipeline methods suffer from problems caused by machine translation systems. for translation-first systems, @xcite find that machine translation introduces errors for summarizers on news text. in addition, existing machine translation systems show poor performance on conversation text @xcite . for summarization-first systems, translating summaries without conversation context can lead to inconsistent translation, in particular for polysemous words. take c en 2s zh 2 for example. the summary "bob is going to the bank.", where "bank" can be translated into "岸边" (river bank) or "银行" (financial bank), requires models to determine the proper translation by considering conversation context. such issues can be also found in end-to-end systems developed for cross-lingual news summarization and directly using those methods can lead to error propagation @xcite @xcite . thus, more sophisticated designs that take care of conversation natures or data selection strategies that can make better use of silver data are in need. ## task description formally, the task of convsumx challenge asks participants to provide a system that can output a summary in a target language given the input conversation text in a source language. ## conclusion we propose the convsumx challenge to address the task of cross-lingual conversation summarization, with the hope that convsumx can encourage researchers to investigate various methods for conversation summarization beyond english, in particular for low and mid-resource languages, and the frontier of cross-lingual conversation summarization can be pushed further.