instruction:
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.
question:
Our in-house dataset includes manually annotated RE data for 6 languages: English, German, Spanish, Italian, Japanese and Portuguese. The ACE05 dataset includes manually annotated RE data for 3 languages: English, Arabic and Chinese. It defines 7 entity types (Person, Organization, Geo-Political Entity, Location, Facility, Weapon, Vehicle) and 6 relation types between the entities (Agent-Artifact, General-Affiliation, ORG-Affiliation, Part-Whole, Personal-Social, Physical).
Question: What languages do they experiment on?
answer:
English, German, Spanish, Italian, Japanese and Portuguese English, Arabic and Chinese

question:
Traditional text-to-speech (TTS) systems are composed of complex pipelines BIBREF0 , these often include accoustic frontends, duration model, acoustic prediction model and vocoder models. The architecture of our model utilizes RNN-based Seq2Seq model for generating mel spectrogram from text. The architecture is similar to that of Tacotron 2 BIBREF4 Direct comparison of model parameters between ours and the open-source tacotron 2, our model contains 4.5 million parameters, whereas the Tacotron 2 contains around 13 million parameters with default setting. By helping our model learn attention alignment faster, we can afford to use a smaller overall model to achieve similar quality speech quality.
Question: Do they reduce the number of parameters in their architecture compared to other direct text-to-speech models?
answer:
Yes

question:
We then show the tweet text and image and we ask them to classify it in one of 6 categories: No attacks to any community, racist, sexist, homophobic, religion based attacks or attacks to other communities.
Question: What annotations are available in the dataset - tweat used hate speach or not?
answer:
No attacks to any community racist sexist homophobic religion based attacks attacks to other communities