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: In this paper, we proposed an efficient sound classification system using the spectrogram images of sounds. We trained

Keyphrases: sound classification audio

Dataset description:
SONYC-UST-V2: A dataset for urban sound tagging with spatiotemporal information. This dataset is aimed for the development and evaluation of machine listening systems for real-world urban noise monitoring.
Localized Narratives: We propose Localized Narratives, a new form of multimodal image annotations connecting vision and language. We ask annotators to describe an image with their voice while simultaneously hovering their mouse over the region they are describing.
ESC-50: The ESC-50 dataset is a labeled collection of 2000 environmental audio recordings suitable for benchmarking methods of environmental sound classification. It comprises 2000 5s-clips of 50 different classes across natural, human and domestic sounds, again, drawn from Freesound.org.
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: SONYC-UST-V2  B: Localized Narratives  C: ESC-50  D: TUT-SED Synthetic 2016
ESC-50