Birdsong NOIZEUS: Bioacoustics noise reduction benchmark dataset

------------------------------------------------------------------------Birdsong noizeus dataset------------------------------------------------------------------------

Authors: Tim Sainburg & Asaf ZoreaYear: 2024

------------------------------------------------------------------------General information------------------------------------------------------------------------- There are 5 recordings from each of 14 individuals (European starlings) recorded in an acoustically isolated chamber. - For each song, we apply noise at 5 SNR levels (0dB, 5dB, 10dB, 15dB). - There are 8 noise types, each taken from a single noise clip from the "Soundscapes from around the world" dataset.- They are "rain", "town", "wind", "waterfall", "insect", "swamp" "frogscape", "forest"- Each soundscape contains multiple noise sources. - Noise levels were estimated using the pyloudnorm software (Steinmetz et al., 2021)- Audio is provided as waveforms at 44100 samplerate

------------------------------------------------------------------------Data format------------------------------------------------------------------------

- clean    - {bird_name}_{timestamp}.wav- noisy    - {snr}dB        - {bird_name}_{timestamp}_{noise_category}_{snr}.wav- noise_sample    - {snr}dB        - {bird_name}_{timestamp}_{noise_category}_{snr}.wav

`clean` contains the original clean audio.`noisy` contains the song+noise`noise_sample` contains a 1-second sample of noise only. 

Timestamp is in the format YYYY-MM-DD_HH-MM-SS-MILLISECONDS and refers to the time that the song was recorded. 

------------------------------------------------------------------------Data sources------------------------------------------------------------------------

Birdsong---------Birdsong are acoustically isolated songs from 14 European Starlingshttps://zenodo.org/records/3237218

Citation: Arneodo, Z., Sainburg, T., Jeanne, J., & Gentner, T. (2019). An acoustically isolated European starling song library (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3237218

This dataset is available under the following license:-  Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/legalcode)

Noise-----Noise are taken from the Xeno-canto - "Soundscapes from around the world" datasethttps://www.gbif.org/dataset/ff571aeb-46bf-45c4-ad2c-af4d68315765

Citation:Vellinga W (2024). Xeno-canto - Soundscapes from around the world. Xeno-canto Foundation for Nature Sounds. Occurrence dataset https://doi.org/10.15468/9u3zaq accessed via GBIF.org on 2024-10-17.

We sampled 8 soundscapes from this dataset:    1. Rain https://www.gbif.org/occurrence/4523646364        - Virginia        - 457s        - rain, Recording of the feeders in the backyard with a light rain falling on the leaf litter, while a freight train passes by ~1/2 mile away.    2. Town https://xeno-canto.org/696263        - 2:22        -  the closer habitat are greater trees and coniferes ..smaller bushes ...some other Krautgärten ... traffic-noise is to hear..as airplanes,too.        - insects, birds, bells, traffic?, airplane        - Germany    3. Wind https://xeno-canto.org/911773        - 5:29        - Very windy day, grassland to shrubland habitat        - Wisconsin    4. Waterfall https://xeno-canto.org/406993        - 24:02        - sound scenes captured in a river forest with zarzas, hiedras and other matorrales at the edge of a small waterfall.        - Spain    5. Insect https://xeno-canto.org/454914        - 5:45        - Australia        - cicadias, birds,    6. Swanp https://xeno-canto.org/909875        - 2:24        - Swampy area along dirt road/trail. Species Include: American Bullfrog, Cricket Frogs, American Crow, Prothonotary Warbler, Red-winged Blackbird, Indigo Bunting, Northern Cardinal    7. Frogscape https://xeno-canto.org/718213        - 4:42         - European Tree Frog Hyla arborea Green Frog Pelophlyax sp.        - Austrial     8. Forest https://xeno-canto.org/900744         - 3:04        - Sweden        - A beautiful choir with frogs, toads, geese and ducks to enjoy in the darkness a foggy night.                        All noise recordings have one of the following licensesL- Creative Commons Attribution-NonCommercial-ShareAlike 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/)- Creative Commons Attribution-ShareAlike 4.0 (https://creativecommons.org/licenses/by-sa/4.0/)

Additional information about the noise dataset

------------------------------------------------------------------------citations------------------------------------------------------------------------

Steinmetz, C. J., & Reiss, J. (2021, May). pyloudnorm: A simple yet flexible loudness meter in python. In Audio Engineering Society Convention 150. Audio Engineering Society.

Arneodo, Z., Sainburg, T., Jeanne, J., & Gentner, T. (2019). An acoustically isolated European starling song library (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3237218

Vellinga W (2024). Xeno-canto - Soundscapes from around the world. Xeno-canto Foundation for Nature Sounds. Occurrence dataset https://doi.org/10.15468/9u3zaq accessed via GBIF.org on 2024-10-17.

# 鸟鸣噪声数据集（Birdsong noizeus dataset）
作者：蒂姆·桑伯格（Tim Sainburg）与阿萨夫·佐雷亚（Asaf Zorea） 年份：2024年

## 基本信息
本数据集包含14只欧洲椋鸟（European starlings）的各5段录音，所有录音均在声学隔离舱内录制。
- 针对每段鸣唱，我们会以5种信噪比（SNR）水平添加噪声，分别为0dB、5dB、10dB、15dB。
- 共使用8类噪声，每类噪声均取自“全球声景（Soundscapes from around the world）”数据集内的单段噪声片段。
- 8类噪声分别为：降雨、城镇环境、风声、瀑布声、虫鸣、Swanp（疑似拼写错误，应为Swamp，沼泽）、蛙群声（frogscape）与森林声。
- 每段声景均包含多种噪声源。
- 噪声水平通过pyloudnorm软件（Steinmetz等人，2021）估算得到。
- 音频以44100Hz采样率的波形文件形式提供。

## 数据格式
数据集分为三个目录：
- `clean`目录：文件命名格式为`{bird_name}_{timestamp}.wav`，存放原始无噪音频。
- `noisy`目录：下设子目录`{snr}dB`，文件命名格式为`{bird_name}_{timestamp}_{noise_category}_{snr}.wav`，存放添加噪声后的鸣唱+噪声音频。
- `noise_sample`目录：下设子目录`{snr}dB`，文件命名格式为`{bird_name}_{timestamp}_{noise_category}_{snr}.wav`，存放仅含噪声的1秒采样片段。

时间戳格式为`YYYY-MM-DD_HH-MM-SS-MILLISECONDS`，对应鸣唱的录制时刻。

## 数据来源
### 鸟鸣音频
本数据集的鸟鸣音频为14只欧洲椋鸟的声学隔离式鸣唱片段，源自以下数据集：
https://zenodo.org/records/3237218
引用信息：Arneodo, Z., Sainburg, T., Jeanne, J., & Gentner, T. (2019). 声学隔离式欧洲椋鸟鸣唱库（版本v1）[数据集]. Zenodo. https://doi.org/10.5281/zenodo.3237218
本数据集采用知识共享署名4.0国际许可协议（Creative Commons Attribution 4.0 International，https://creativecommons.org/licenses/by/4.0/legalcode）进行授权。

### 噪声片段
噪声片段源自Xeno-canto的“全球声景”数据集：
https://www.gbif.org/dataset/ff571aeb-46bf-45c4-ad2c-af4d68315765
引用信息：Vellinga W (2024). Xeno-canto - 全球声景. Xeno-canto自然声音基金会. 出现数据集 https://doi.org/10.15468/9u3zaq，于2024-10-17通过GBIF.org获取。

本数据集共从该源数据集中采样8段声景：
1. **降雨（Rain）**：https://www.gbif.org/occurrence/4523646364，采集地：美国弗吉尼亚州，时长457秒，场景为后院落叶层上的小雨声，同时远处约0.8公里处有货运列车驶过，背景包含喂食器的录音。
2. **城镇环境（Town）**：https://xeno-canto.org/696263，时长2分22秒，周边生境包含高大乔木、针叶树、小型灌丛与部分菜园，可听到交通噪声、飞机声，背景还有昆虫、鸟类与钟声。采集地：德国。
3. **风声（Wind）**：https://xeno-canto.org/911773，时长5分29秒，拍摄于大风天气下的草原至灌丛生境，采集地：美国威斯康星州。
4. **瀑布声（Waterfall）**：https://xeno-canto.org/406993，时长24分02秒，录制于河流森林中的小型瀑布边缘，包含荆棘、常春藤与其他灌丛，采集地：西班牙。
5. **虫鸣（Insect）**：https://xeno-canto.org/454914，时长5分45秒，采集地：澳大利亚，背景包含蝉鸣与鸟类鸣唱。
6. **Swanp**：https://xeno-canto.org/909875，时长2分24秒，场景为土路/步道旁的沼泽区域，物种包括美洲牛蛙、蟋蟀蛙、美洲乌鸦、原食虫莺、红翅黑鹂、靛蓝彩鹀、北美主红雀。
7. **蛙群声（frogscape）**：https://xeno-canto.org/718213，时长4分42秒，包含欧洲树蛙（*Hyla arborea*）、绿蛙（*Pelophlyax* sp.），采集地：澳大利亚（原文疑似拼写错误，应为Australia）。
8. **森林声（Forest）**：https://xeno-canto.org/900744，时长3分04秒，采集地：瑞典，场景为雾夜中蛙类、蟾蜍、鹅与鸭组成的悦耳鸣唱合声。

所有噪声录音采用以下两种许可协议之一：
- 知识共享署名-非商业性使用-相同方式共享4.0国际许可协议（https://creativecommons.org/licenses/by-nc-sa/4.0/）
- 知识共享署名-相同方式共享4.0国际许可协议（https://creativecommons.org/licenses/by-sa/4.0/）

### 噪声数据集补充说明

## 引用文献
1. Steinmetz, C. J., & Reiss, J. (2021, 5月). pyloudnorm：一款简洁灵活的Python响度计. 第150届音频工程学会大会. 音频工程学会.
2. Arneodo, Z., Sainburg, T., Jeanne, J., & Gentner, T. (2019). 声学隔离式欧洲椋鸟鸣唱库（版本v1）[数据集]. Zenodo. https://doi.org/10.5281/zenodo.3237218
3. Vellinga W (2024). Xeno-canto - 全球声景. Xeno-canto自然声音基金会. 出现数据集 https://doi.org/10.15468/9u3zaq，于2024-10-17通过GBIF.org获取。