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.

Ex Input:
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 open source LJSpeech Dataset was used to train our TTS model. The architecture of our model utilizes RNN-based Seq2Seq model for generating mel spectrogram from text

Ex Output:
Which dataset(s) do they evaluate on?


Ex Input:
Follow the prior works BIBREF6, BIBREF7, BIBREF9, we adopt the BLEU and the Micro Entity F1 to evaluate our model performance.  We provide human evaluation on our framework and the compared models.  We hire several human experts and ask them to judge the quality of the responses according to correctness, fluency, and humanlikeness on a scale from 1 to 5.

Ex Output:
What were the evaluation metrics?


Ex Input:
The MCD splits achieve a significantly higher compound divergence at a similar atom divergence when compared to the other experiments. 

Ex Output:

What are results of comparison between novel method to other approaches for creating compositional generalization benchmarks?