You are provided with a research question, keyphrases about the question, a description of candidate datasets and dataset options. Read the description of popular datasets provided below and select the ones that can be used to validate the following research question. Use your knowledge of machine learning datasets to make the best judgement.
Your response should be formatted as a `json` array. For instance, for the query "Semi supervised image classification", a sample response might be: ["CIFAR-10", "CIFAR-100"]. Do not include any extra text in the response other than the answer array.

Query: A system for action quality assessment.

Keyphrases: action evaluation video

Dataset description:
AQA-7: Consists of 1106 action samples from seven actions with quality scores as measured by expert human judges.
WMT 2016: WMT 2016 is a collection of datasets used in shared tasks of the First Conference on Machine Translation. The conference builds on ten previous Workshops on statistical Machine Translation.
LIVE-YT-HFR: LIVE-YT-HFR comprises of 480 videos having 6 different frame rates, obtained from 16 diverse contents.
LIVE1: Quality Assessment research strongly depends upon subjective experiments to provide calibration data as well as a testing mechanism. After all, the goal of all QA research is to make quality predictions that are in agreement with subjective opinion of human observers.
Kinetics: The Kinetics dataset is a large-scale, high-quality dataset for human action recognition in videos. The dataset consists of around 500,000 video clips covering 600 human action classes with at least 600 video clips for each action class.
FineGym: FineGym is an action recognition dataset build on top of gymnasium videos. Compared to existing action recognition datasets, FineGym is distinguished in richness, quality, and diversity.
Charades: The Charades dataset is composed of 9,848 videos of daily indoors activities with an average length of 30 seconds, involving interactions with 46 objects classes in 15 types of indoor scenes and containing a vocabulary of 30 verbs leading to 157 action classes. Each video in this dataset is annotated by multiple free-text descriptions, action labels, action intervals and classes of interacting objects.

Options:- A: AQA-7  B: WMT 2016  C: LIVE-YT-HFR  D: LIVE1  E: Kinetics  F: FineGym  G: Charades
["AQA-7", "Charades"]