Given a short query with keyphrases about a research idea in 2020 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 analyze Western and Chinese classical music through machine learning models. Specifically, we apply sound event detection

Keyphrases: soundscape emotion recognition audio

Dataset description:
TUT Sound Events 2017: The TUT Sound Events 2017 dataset contains 24 audio recordings in a street environment and contains 6 different classes. These classes are: brakes squeaking, car, children, large vehicle, people speaking, and people walking.
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.
ReCAM: Tasks Our shared task has three subtasks. Subtask 1 and 2 focus on evaluating machine learning models' performance with regard to two definitions of abstractness (Spreen and Schulz, 1966; Changizi, 2008), which we call imperceptibility and nonspecificity, respectively.
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.

Options:- A: TUT Sound Events 2017  B: AudioSet  C: ReCAM  D: TUT-SED Synthetic 2016
AudioSet