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.

[EX Q]: We explored different normalization techniques. FBanks with cepstral mean normalization (CMN) perform better than raw FBanks. We found using variance with mean normalization (CMVN) unnecessary for the task. Using deltas and delta-deltas improves model, so we used them in other experiments. Models trained with spectrogram features converge slower and to worse minimum, but the difference when using CMN is not very big compared to FBanks. 
 Question: What normalization techniques are mentioned?
[EX A]: FBanks with cepstral mean normalization (CMN) variance with mean normalization (CMVN)

[EX Q]: Figure FIGREF23 shows the proposed ontology, which, in our evaluation procedure, was populated with 3121 events entries from 51 documents. 
 Question: How is the effectiveness of this pipeline approach evaluated?
[EX A]: proposed ontology, which, in our evaluation procedure, was populated with 3121 events entries from 51 documents.

[EX Q]: We used two datasets for the task - AMR Bank BIBREF10 and CNN-Dailymail ( BIBREF11 BIBREF12 ).  
 Question: What dataset is used in this paper?
[EX A]:
AMR Bank CNN-Dailymail