In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

Input: Consider Input: In this paper, we first highlight the importance of TV and radio broadcast as a source of data for ASR, and the potential impact it can have. We then perform a statistical analysis of gender representation in a data set composed of four state-of-the-art corpora of French broadcast, widely used within the speech community. Finally we question the impact of such a representation on the systems developed on this data, through the perspective of an ASR system.

Output: What tasks did they use to evaluate performance for male and female speakers?


Input: Consider Input: Paraphrase Identification (PI) is the task of determining whether two sentences are paraphrase or not. We have implemented the cross-lingual variant of kernel functions for PI and RE tasks as described in section SECREF3 and measured the accuracy of models by testing them on the parallel data set.

Output: What classification task was used to evaluate the cross-lingual adaptation method described in this work?


Input: Consider Input: We use 10-fold cross-validation, and only two types of features: n-grams and Word2Vec word embeddings.  The n-gram features include unigrams, bigrams, and trigrams, including sequences of punctuation (for example, ellipses or "!!!"), and emoticons. We use GoogleNews Word2Vec features BIBREF28 .


Output: What simple features are used?