https://github.com/mbari-org/pacific-sound-notebooks

Juptyer notebook tutorials on using the data in the AWS pacific-sound registry for ocean soundscape research, education, and the arts
https://github.com/mbari-org/pacific-sound-notebooks

acoustics aws bluewhale deep-learning humpback humpback-whale machine-learning marine-data open-access open-data open-datasets open-science python

Last synced: about 2 months ago
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Juptyer notebook tutorials on using the data in the AWS pacific-sound registry for ocean soundscape research, education, and the arts

• Host: GitHub
• URL: https://github.com/mbari-org/pacific-sound-notebooks
• Owner: mbari-org
• License: gpl-3.0
• Created: 2021-10-10T18:23:17.000Z (over 3 years ago)
• Default Branch: master
• Last Pushed: 2024-01-08T19:28:11.000Z (about 1 year ago)
• Last Synced: 2024-12-07T17:05:00.652Z (about 2 months ago)
• Topics: acoustics, aws, bluewhale, deep-learning, humpback, humpback-whale, machine-learning, marine-data, open-access, open-data, open-datasets, open-science, python
• Homepage: https://docs.mbari.org/pacific-sound
• Size: 37.4 MB
• Stars: 22
• Watchers: 8
• Forks: 6
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
[![MBARI](https://www.mbari.org/wp-content/uploads/2014/11/logo-mbari-3b.png)](http://www.mbari.org)

 

## 
About


Tutorials written in [Jupyter Notebooks](https://jupyter.org) to guide you through both accessing and 

using the data in the AWS [pacific-sound registry](https://registry.opendata.aws/pacific-sound).

 

Tutorials

 

## Data Notebooks

 

* [2kHz Data](https://github.com/mbari-org/pacific-sound-notebooks/blob/master/docs/notebooks/data/PacificSound2kHz.ipynb) ✨ Recommended first step to learn more about the low-frequency data

* [16kHz Data](https://github.com/mbari-org/pacific-sound-notebooks/blob/master/docs/notebooks/data/PacificSound16kHz.ipynb) ✨ Recommended first step to learn more about the low-mid-frequency data

* [256kHz Data](https://github.com/mbari-org/pacific-sound-notebooks/blob/master/docs/notebooks/data/PacificSound256kHz.ipynb) ✨ Recommended first step to learn more about the raw 10-minute data

* [256kHz to 2kHz Decimation](https://github.com/mbari-org/pacific-sound-notebooks/blob/master/docs/notebooks/data/PacificSound256kHzTo2kHzDecimate.ipynb) ✨ Recommended to learn about how the raw 10-minute data is decimated from 256kHz to 2Khz

## Research and Machine Learning Notebooks

 

  * Blue Whales

      * [Blue B call index 🐳](https://github.com/mbari-org/pacific-sound-notebooks/blob/master/docs/notebooks/bluewhales/classify/blueB/PacificSoundBlueBCallIndex.ipynb) Study song occurrence using a signal processing method

      * [Blue A call classification 🐳](https://github.com/mbari-org/pacific-sound-notebooks/blob/master/docs/notebooks/bluewhales/classify/blueA/PacificSoundClassifyBlueA.ipynb) Classify blue whale song A calls with a neural network model

  * Fin Whales

    * [Fin whale call index 🐳](https://github.com/mbari-org/pacific-sound-notebooks/blob/master/docs/notebooks/finwhales/PacificSound_FinCallindex.ipynb) Fin whale song occurrence using a signal processing method

  * Humpback Whales

      * [Humpback whale song detection 🐳](https://github.com/mbari-org/pacific-sound-notebooks/blob/master/docs/notebooks/humpbackwhales/detect/PacificSoundDetectHumpbackSong.ipynb) Detect humpback song with a neural network model

  * Shipping Noise

    - [Quantify shipping noise in the soundscape](https://github.com/mbari-org/pacific-sound-notebooks/blob/master/docs/notebooks/shippingnoise/PacificSoundShippingNoiseAnalysis.ipynb) 🛳️ Apply international standards to measure shipping noise and its temporal variations.

 

## Listen Up

* [Full access to 16 kHz audio](https://github.com/mbari-org/pacific-sound-notebooks/blob/master/docs/notebooks/listen/PacificSoundListen.ipynb) 🐬  Listen to example recordings of dolphins and whales, then pick any time to listen and explore.

## 
Documentation
 


See [pacific-sound](http://docs.mbari.org/pacific-sound) for the official documentation.

## 
Quick Start 

 

### [Install in SageMaker](https://docs.mbari.org/pacific-sound/installation/sagemaker/)


### [Install in Colab](https://docs.mbari.org/pacific-sound/installation/colab/)

 

### Install in your computer

[**Python>=3.6.0**](https://www.python.org/) is required with the 

[requirements.txt](https://github.com/mbari-org/pacific-sound-notebooks/blob/master/docs/notebooks/requirements.txt).

 

The recommended way to run the notebooks is using the [Anaconda](https://www.anaconda.com/) environment

```bash

git clone https://github.com/mbari-org/pacific-sound-notebooks

cd pacific-sound-notebooks

```

If using a Mac 

```

brew install sox

```

If using Linux

```

apt-get install libsox-fmt-all libsox-dev

```

```

conda env create 

conda activate pacific-sound-notebooks

pip install ipykernel

python -m ipykernel install --user --name=pacific-sound-notebooks

jupyter notebook

```