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: I want to train a semi-supervised model for audio-visual speech

Keyphrases: audio-visual speech recognition video

Dataset description:
LRS2: The Oxford-BBC Lip Reading Sentences 2 (LRS2) dataset is one of the largest publicly available datasets for lip reading sentences in-the-wild. The database consists of mainly news and talk shows from BBC programs.
LRW: The Lip Reading in the Wild (LRW) dataset  a large-scale audio-visual database that contains 500 different words from over 1,000 speakers. Each utterance has 29 frames, whose boundary is centered around the target word.
YouTube-8M: The YouTube-8M dataset is a large scale video dataset, which includes more than 7 million videos with 4716 classes labeled by the annotation system. The dataset consists of three parts: training set, validate set, and test set.
Libri-Light: Libri-Light is a collection of spoken English audio suitable for training speech recognition systems under limited or no supervision. It is derived from open-source audio books from the LibriVox project.
VoxCeleb2: VoxCeleb2 is a large scale speaker recognition dataset obtained automatically from open-source media. VoxCeleb2 consists of over a million utterances from over 6k speakers.
AVE: To investigate three temporal localization tasks: supervised and weakly-supervised audio-visual event localization, and cross-modality localization.

Options:- A: LRS2  B: LRW  C: YouTube-8M  D: Libri-Light  E: VoxCeleb2  F: AVE
["LRS2", "LRW"]