In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

Q: As a document classifier we employ a word-based CNN similar to Kim consisting of the following sequence of layers: $ \texttt {Conv} \xrightarrow{} \texttt {ReLU} \xrightarrow{} \texttt {1-Max-Pool} \xrightarrow{} \texttt {FC} \\ $ Future work would include applying LRP to other neural network architectures (e.g. character-based or recurrent models) on further NLP tasks, as well as exploring how relevance information could be taken into account to improve the classifier's training procedure or prediction performance.

A: Do the experiments explore how various architectures and layers contribute towards certain decisions?
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Q: We used recordings of nurse-initiated telephone conversations for congestive heart failure patients undergoing telemonitoring, post-discharge from the hospital. To analyze the linguistic structure of the inquiry-response pairs in the entire 41-hour dataset, we randomly sampled a seed dataset consisting of 1,200 turns and manually categorized them to different types, which are summarized in Table TABREF14 along with the corresponding occurrence frequency statistics.

A: Which data do they use as a starting point for the dialogue dataset?
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Q: All the datasets consist of videos where only one speaker is in front of the camera. The descriptors we used for each of the modalities are as follows: Language All the datasets provide manual transcriptions. Vision Facet BIBREF26 is used to extract a set of features including per-frame basic and advanced emotions and facial action units as indicators of facial muscle movement. Acoustic We use COVAREP BIBREF27 to extract low level acoustic features including 12 Mel-frequency cepstral coefficients (MFCCs), pitch tracking and voiced/unvoiced segmenting features, glottal source parameters, peak slope parameters and maxima dispersion quotients.

A:
What modalities are being used in different datasets?
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