In this task, you will be presented with a context from an academic paper and a question based on the context. You have to classify the questions into "Extractive", "Abstractive", or "Yes-no" questions. Extractive questions can be answered by concatenating extracts taken from a context into a summary while answering abstractive questions involves paraphrasing the context using novel sentences. Yes-no question is a question whose expected answer is one of two choices, one that affirms the question and one that denies the question. Typically, the choices are either yes or no.

Q: In our experiments, the RNN takes in spectrograms of utterances, passing them through two 2D-convolutional layers, followed by seven bi-directional recurrent layers and a fully-connected layer with softmax activation. All recurrent layers are batch normalized. At each timestep, the softmax activations give a probability distribution over the characters. CTC loss BIBREF8 is then computed from the timestep-wise probabilities. 
 Question: Which model do they use for end-to-end speech recognition?

A: Extractive
****
Q: One of the solutions that has been proposed for mitigating gender bias on the word embedding level is Counterfactual Data Augmentation (CDA) BIBREF25. We apply this method by augmenting our dataset with a copy of every dialogue with gendered words swapped using the gendered word pair list provided by BIBREF21. 
 Question: How does counterfactual data augmentation aim to tackle bias?

A: Abstractive
****
Q: Many NLP tasks utilize POS as features, but human annotated POS sequences are difficult and expensive to obtain. Thus, it is important to know if we can learn sentences-level syntactic embeddings for low-sources languages without treebanks.

We performed zero-shot transfer of the syntactic embeddings for French, Portuguese and Indonesian. French and Portuguese are simulated low-resource languages, while Indonesian is a true low-resource language. 
 Question: Do they evaluate on downstream tasks?

A:
Yes-no
****