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Browse files- README.md +135 -0
- audioset2022.py +20 -0
README.md
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---
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license: cc-by-sa-4.0
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---
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---
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license: cc-by-sa-4.0
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annotations_creators:
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- unknown
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language_creators:
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- unknown
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size_categories:
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- 100K<n<100M
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source_datasets:
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- unknown
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task_categories:
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- audio-classification
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task_ids:
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- other-audio-slot-filling
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---
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# Dataset Card for audioset2022
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## Table of Contents
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Annotations](#annotations)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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- **Homepage:** [AudioSet Ontology](https://research.google.com/audioset/ontology/index.html)
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- **Repository:** [Needs More Information]
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- **Paper:** [Audio Set: An ontology and human-labeled dataset for audio events](https://research.google.com/pubs/pub45857.html)
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- **Leaderboard:** [Paperswithcode Leaderboard](https://paperswithcode.com/dataset/audioset)
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### Dataset Summary
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The AudioSet ontology is a collection of sound events organized in a hierarchy. The ontology covers a wide range of everyday sounds, from human and animal sounds, to natural and environmental sounds, to musical and miscellaneous sounds.
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**This repository only includes audio files for DCASE 2022 - Task 3**
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### Supported Tasks and Leaderboards
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- `audio-classification`: The dataset can be used to train a model for Sound Event Detection/Localization.
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**The recordings only includes the single channel audio. For Localization tasks, it will required to apply RIR information**
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### Languages
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None
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## Dataset Structure
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### Data Instances
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**WIP**
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```
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{
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'file':
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}
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```
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### Data Fields
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- file: A path to the downloaded audio file in .mp3 format.
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### Data Splits
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This dataset only includes audio file from the unbalance train list.
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The data comprises two splits: weak labels and strong labels.
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## Dataset Creation
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### Curation Rationale
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[Needs More Information]
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### Source Data
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#### Initial Data Collection and Normalization
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[Needs More Information]
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#### Who are the source language producers?
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[Needs More Information]
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### Annotations
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#### Annotation process
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[Needs More Information]
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#### Who are the annotators?
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[Needs More Information]
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### Personal and Sensitive Information
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[Needs More Information]
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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### Discussion of Biases
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[More Information Needed]
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### Other Known Limitations
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[Needs More Information]
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## Additional Information
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### Dataset Curators
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The dataset was initially downloaded by Nelson Yalta ([email protected]).
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### Licensing Information
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[CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0)
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### Citation Information
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```
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@inproceedings{45857,
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title = {Audio Set: An ontology and human-labeled dataset for audio events},
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author = {Jort F. Gemmeke and Daniel P. W. Ellis and Dylan Freedman and Aren Jansen and Wade Lawrence and R. Channing Moore and Manoj Plakal and Marvin Ritter},
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year = {2017},
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booktitle = {Proc. IEEE ICASSP 2017},
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address = {New Orleans, LA}
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}
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```
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audioset2022.py
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# coding=utf-8
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# Copyright 2022 Nelson Yalta (Hitachi Ltd.)
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Speech Commands, an audio dataset of spoken words designed to help train and evaluate keyword spotting systems. """
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import datasets
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