
Description This dataset comprises embeddings and captions utilized as the development dataset for DCASE 2024 Challenge Task 7, focusing on 'Environmental Sound Scene Synthesis.' The embeddings are derived from 60 different 4-second audio files formatted as mono 32-bit 32kHz, and are contained in the 'embeddings.tar.xz' file. Captions corresponding to each audio file can be found in 'caption.csv'. This dataset does not comprise the audio files, only the embeddings. Three different types of embeddings are provided: VGGish (vggish), MS-CLAP (clap-2023), and PANNs CNN14 Wavegram-Logmel (panns-wavegram-logmel). Only PANNs CNN14 Wavegram-Logmel (panns-wavegram-logmel) embeddings are used for evaluation in the challenge. For further details, please refer to the challenge website. Contact Modan Tailleur, modan.tailleur@ls2n.fr Mathieu Lagrange, mathieu.lagrange@ls2n.fr
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
