General information | |||||
| Label | Value | Description | |||
|---|---|---|---|---|---|
| Name | FSDnoisy18k | Full dataset name | |||
| ID | sounds/fsdnoisy18k | Datalist id for external indexing | |||
| Abbreviation | FSDnoisy18k | Official dataset abbreviation, e.g. one used in the original paper | |||
| Provider | UPF | ||||
| Year | 2019 | Dataset release year | |||
| Modalities | Audio | Data modalities included in the dataset | |||
| Collection name | FSD | Common name for all related datasets, used to group datasets coming from same source | |||
| Research domain | Tagging Weak annotation Noisy labels | Related domains, e.g., Scenes, Mobile devices, Audio-visual, Open set, Ambient noise, Unlabelled, Multiple sensors, SED, SELD, Tagging, FL, Strong annotation, Weak annotation, Unlabelled, Multi-annotator | |||
| License | Creative Commons | ||||
| Download | Download (9.5GB) | ||||
| Companion site | Site | Link to the companion site for the dataset | |||
| Citation | [Fonseca2019] Learning Sound Event Classifiers from Web Audio with Noisy Labels | ||||
Audio | |||||
| Label | Value | Description | |||
Data | |||||
| Data type | Audio | Possible values: Audio | Features | |||
File format | |||||
| File format type | Constant | Possible values: Constant | Variable | |||
| File format | wav | Possible value: wav | aiff | flac | mp3 | aac | ogg | |||
Channels | |||||
| Setup | Mono | Possible values: Mono | Stereo | Binaural | Ambisonic | Array | Multi-Channel | Variable | |||
| Number of channels | 1 | ||||
Material | |||||
| Source | Freesound | Possible values: Original | Youtube | Freesound | Online | Crowdsourced | [Dataset name] | |||
Content | |||||
| Content type | Freefield | Possible values: Freefield | Synthetic | Isolated | |||
Recording | |||||
Files | |||||
| Count | 18533 files | Total number of files | |||
| Total duration (minutes) | 2550 min | Total duration of the dataset in minutes | |||
| File length | Variable | Characterization of the file lengths, possible values: Constant | Quasi-constant | Variable | |||
Meta | |||||
| Label | Value | Description | |||
| Types | Tag | List of meta data types provided for the data, possible values: Event, Tag, Scene, Caption, Geolocation, Spatial location, Annotator, Timestamp, Presence, Proximity, etc. | |||
Scene | |||||
Event | |||||
| Classes | 20 | Number of event classes | |||
Annotation | |||||
| Type | Weak | Possible values: Strong | Weak | Location | None | |||
| Source | Crowdsourced | Possible values: Experts | Crowdsourced | Synthetic | Metadata | Automatic | |||
| Annotations per item | 1 | How many annotations there are available per item (possible multi-annotator setup) | |||
| Labelled amount (%) | 100 % | Percentage of all data, amount of data which is labelled | |||
| Validated amount (%) | 14.671127179 % | Percentage of all data, amount of data which is validated by human | |||
| Strong annotations amount (%) | 0 % | Percentage of all data, amount of data which has strong annotations | |||
| Overlapping event instances | Yes | ||||
Labeling | |||||
| Hierarchical | Yes | ||||
| Ontology name | Yes | ||||
Instance | |||||
| Count | 18533 | Count of all event instances in the dataset | |||
| Average instances per class | 926.65 | Average per class instance count | |||
Cross-validation setup | |||||
| Label | Value | Description | |||
| Provided | Yes | ||||
| Folds | 1 | ||||
| Sets | Train Test | Set types provided in the split, possible values: Train | Test | Val | Dev | Eval | |||
Baseline | |||||
| Label | Value | Description | |||
| Download | Download | Link to baseline system source code | |||
| Citation | [Fonseca2019] | Paper to cite for the baseline | |||