TASK DEFINITION: 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.
PROBLEM: A simple, yet recurrent text model is the well-known word co-occurrence network. After optional textual pre-processing steps, in a co-occurrence network each different word becomes a node and edges are established via co-occurrence in a desired window. A common strategy connects only adjacent words in the so called word adjacency networks. 
 Question: On what model architectures are previous co-occurence networks based?

SOLUTION: in a co-occurrence network each different word becomes a node and edges are established via co-occurrence in a desired window connects only adjacent words in the so called word adjacency networks

PROBLEM: Results show that the CJFA encoder obtains significantly better phone classification accuracy than the VAE baseline and also than the CJFS encoder. These results are replicated for speaker recognition tasks. 
 Question: Which approach out of two proposed in the paper performed better in experiments?

SOLUTION: CJFA encoder 

PROBLEM: Two metrics, the accuracy (ACC) and the normalized mutual information metric (NMI), are used to measure the clustering performance BIBREF38 , BIBREF48 .  
 Question: What were the evaluation metrics used?

SOLUTION:
accuracy normalized mutual information