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.

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?
FBanks with cepstral mean normalization (CMN) variance with mean normalization (CMVN)

VQA research began in earnest in late 2014 when the DAQUAR dataset was released BIBREF0
Question: From when are many VQA datasets collected?
late 2014

Attention-base translation model We use the system of BIBREF6 , a convolutional sequence to sequence model.
Question: Which translation system do they use to translate to English?
Attention-based translation model with convolution sequence to sequence model