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.

Example Input: We adopt a DNN-based acoustic model BIBREF0 with 11 hidden layers and the alignment used to train the model is derived from a HMM-GMM model trained with SAT criterion. 
 Question: What are the deep learning architectures used in the task?
Example Output: DNN-based acoustic model BIBREF0

Example Input: The annotation process was a trial-and-error, with cycles composed of annotation, discussing confusing entities, updating the annotation guide schematic and going through the corpus section again to correct entities following guide changes. 
 Question: Did they experiment with the corpus?
Example Output: Yes

Example Input: We showed in BIBREF22 that Pearson correlation is badly suited for STS. Instead, we compute the Spearman's rank correlation between the cosine-similarity of the sentence embeddings and the gold labels. 
 Question: What metrics are used for the STS tasks?
Example Output:
 Spearman's rank correlation between the cosine-similarity of the sentence embeddings and the gold labels