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.

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?
MLP

To study the lexical and semantic diversities of responses, we performed three analyses. First, we aggregated all worker responses to a particular question into a single list corresponding to that question. Second, we compared the diversity of individual responses between Control and AUI for each question. To measure diversity for a question, we computed the number of responses divided by the number of unique responses to that question. We call this the response density.  
 Question: How was lexical diversity measured?
By computing number of unique responses and number of responses divided by the number of unique responses to that question for each of the questions

In multitask learning, a set of related tasks are learned (e.g., emotional activation), along with a primary task (e.g., emotional valence); both tasks share parts of the network topology and are hence jointly trained, as depicted in Figure FIGREF4 . 
 Question: What are the tasks in the multitask learning setup?

set of related tasks are learned (e.g., emotional activation) primary task (e.g., emotional valence)