Given a short query with keyphrases about a research idea in 2019 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.

Query: I want to build a system for talking head generation.

Keyphrases: audio-driven talking head generation video

Dataset description:
Frames Dataset: This dataset is dialog dataset collected in a Wizard-of-Oz fashion. Two humans talked to each other via a chat interface.
SNIPS: The SNIPS Natural Language Understanding benchmark is a dataset of over 16,000 crowdsourced queries distributed among 7 user intents of various complexity:   SearchCreativeWork (e.g. Find me the I, Robot television show), GetWeather (e.g.
MuST-Cinema: MuST-Cinema is a Multilingual Speech-to-Subtitles corpus ideal for building subtitle-oriented machine and speech translation systems. It comprises audio recordings from English TED Talks, which are automatically aligned at the sentence level with their manual transcriptions and translations.
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.

Options:- A: Frames Dataset  B: SNIPS  C: MuST-Cinema  D: LRW
LRW