Given a short query with keyphrases about a research idea in 2018 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: We propose an approach for weakly supervised training of sound event detection.

Keyphrases: sound event detection audio

Dataset description:
TUT-SED Synthetic 2016: TUT-SED Synthetic 2016 contains of mixture signals artificially generated from isolated sound events samples. This approach is used to get more accurate onset and offset annotations than in dataset using recordings from real acoustic environments where the annotations are always subjective.
AudioSet: Audioset is an audio event dataset, which consists of over 2M human-annotated 10-second video clips. These clips are collected from YouTube, therefore many of which are in poor-quality and contain multiple sound-sources.
AVE: To investigate three temporal localization tasks: supervised and weakly-supervised audio-visual event localization, and cross-modality localization.
TableBank: To address the need for a standard open domain table benchmark dataset, the author propose a novel weak supervision approach to automatically create the TableBank, which is orders of magnitude larger than existing human labeled datasets for table analysis. Distinct from traditional weakly supervised training set, our approach can obtain not only large scale but also high quality training data.

Options:- A: TUT-SED Synthetic 2016  B: AudioSet  C: AVE  D: TableBank
AudioSet