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.

Q: We evaluated the proposed model using the publicly available LibriSpeech ASR corpus BIBREF23. The LibriSpeech dataset consists of 970 hours of audio data with corresponding text transcripts (around 10M word tokens) and an additional 800M word token text only dataset. 
 Question: How big is LibriSpeech dataset?

A: 970 hours of audio data with corresponding text transcripts (around 10M word tokens) and an additional 800M word token text only dataset
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Q: The dataset includes about 6,000 triples, comprised of videos, questions, and answer spans manually collected from screencast tutorial videos with spoken narratives for a photo-editing software.  
 Question: What kind of instructional videos are in the dataset?

A: tutorial videos for a photo-editing software
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Q: We evaluate our cross-lingual pre-training based transfer approach against several strong baselines on two public datatsets, Europarl BIBREF31 and MultiUN BIBREF32, which contain multi-parallel evaluation data to assess the zero-shot performance. 
 Question: which datasets did they experiment with?

A:
Europarl MultiUN
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