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.

[Q]: Despite these shortcomings in using WER as a metric of success, the WER can reflect our model's effectiveness in generating questions that are similar to those of SQuAD based on the given reading passage and answer. WER can be used for initial analyses that can lead to deeper insights as discussed further below. 
 Question: Why did they choose WER as evaluation metric?
[A]: WER can reflect our model's effectiveness in generating questions that are similar to those of SQuAD WER can be used for initial analyses


[Q]: Table TABREF14 show the results obtained for proposed s2sL approach in comparison to that of MLP for the tasks of Speech/Music and Neutral/Sad classification, by considering different proportions of training data. 
 Question: Which models/frameworks do they compare to?
[A]: MLP


[Q]: We introduce a list of 8 different competencies that a reading system should master in order to process reviews and text documents in general. These 8 tasks require different competencies and a different level of understanding of the document to be well answered. For instance, detecting if an aspect is mentioned in a review will require less understanding of the review than predicting explicitly the rating of this aspect. Table TABREF10 presents the 8 tasks we have introduced in this dataset with an example of a question that corresponds to each task. 
 Question: What kind of questions are present in the dataset?
[A]:
These 8 tasks require different competencies and a different level of understanding of the document to be well answered