In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
One example is below.
Q: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequence model. Large-Scale Chinese Short Text Summarization Dataset (LCSTS) is constructed by BIBREF1 . The dataset consists of more than 2.4 million text-summary pairs in total, constructed from a famous Chinese social media microblogging service Weibo.
Question: Are results reported only for English data?
A: No
Rationale: Based on the context, the dataset is constructed from a famous Chinese social media microblogging service Weibo.
Q: Furthermore, the gains in WER over the baseline are significantly larger for the Density Ratio method than for Shallow Fusion, with up to 28% relative reduction in WER (17.5% $
ightarrow $ 12.5%) compared to up to 17% relative reduction (17.5% $
ightarrow $ 14.5%) for Shallow Fusion, in the no fine-tuning scenario.
Question: What metrics are used for evaluation?
A:
word error rate