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.

Ex Input:
For the labeled data, we use audio from the IEMOCAP dataset, which comes with labels for activation and valence, both measured on a 5-point Likert scale from three distinct annotators.

Ex Output:
Which multitask annotated corpus is used?


Ex Input:
o evaluate the quality of the generated sequences regarding both precision and recall, the evaluation metrics include BLEU and ROUGE (1, 2, L) scores with multiple references BIBREF22 .

Ex Output:
What evaluation metrics are used?


Ex Input:
Using an encoder-decoder backbone, our model may be regarded as an extension of the constituent parsing model of BIBREF18 as shown in Figure FIGREF4. The difference is that in our model both constituent and dependency parsing share the same token representation and shared self-attention layers and each has its own individual Self-Attention Layers and subsequent processing layers. Our model includes four modules: token representation, self-attention encoder, constituent and dependency parsing decoder. Constituent Parsing Decoder Dependency Parsing Decoder

Ex Output:

What are the models used to perform constituency and dependency parsing?