{
  "id": 197740,
  "title": "Research Papers and Previous works Placeholder",
  "url": "/competitions/rfcx-species-audio-detection/discussion/197740",
  "author_name": "",
  "post_date": "2020-11-17T21:28:09.637878500Z",
  "votes": 13,
  "comment_count": 3,
  "views": 0,
  "content": "<p>I am opening this thread for competition-related research papers and previous works, I will keep adding throughout the competition. </p>\n<h1>Audio Detection</h1>\n<ul>\n<li><a href=\"https://arxiv.org/abs/1807.05812\" target=\"_blank\">Automatic acoustic detection of birds through deep learning: the first Bird Audio Detection challenge</a></li>\n<li><a href=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6505557/\" target=\"_blank\">Automatic acoustic identification of individuals in multiple species: improving identification across recording conditions</a></li>\n<li><a href=\"https://www.pnas.org/content/115/25/E5716/\" target=\"_blank\">Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning</a></li>\n<li><a href=\"https://arxiv.org/abs/1912.10211\" target=\"_blank\">PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition</a></li>\n<li><a href=\"https://arxiv.org/abs/1904.08779\" target=\"_blank\">SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition</a></li>\n<li><a href=\"https://ai.googleblog.com/2019/04/specaugment-new-data-augmentation.html\" target=\"_blank\">SpecAugment Google AI Blog</a></li>\n<li><a href=\"https://arxiv.org/pdf/1710.09412.pdf\" target=\"_blank\">mixup: BEYOND EMPIRICAL RISK MINIMIZATION</a></li>\n</ul>\n<h1>Weak Label Learning:</h1>\n<ul>\n<li><a href=\"https://arxiv.org/pdf/1804.09288.pdf\" target=\"_blank\">A Closer Look at Weak Label Learning for Audio Events</a></li>\n</ul>\n<h1>Some benchmarks:</h1>\n<ul>\n<li><a href=\"https://arxiv.org/pdf/2010.10915.pdf\" target=\"_blank\">CONTRASTIVE LEARNING OF GENERAL-PURPOSE AUDIO REPRESENTATIONS (COLA)</a></li>\n</ul>",
  "messages": [
    {
      "id": "1082394",
      "postDate": "11/17/2020 21:28:09",
      "content": "<p>I am opening this thread for competition-related research papers and previous works, I will keep adding throughout the competition. </p>\n<h1>Audio Detection</h1>\n<ul>\n<li><a href=\"https://arxiv.org/abs/1807.05812\" target=\"_blank\">Automatic acoustic detection of birds through deep learning: the first Bird Audio Detection challenge</a></li>\n<li><a href=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6505557/\" target=\"_blank\">Automatic acoustic identification of individuals in multiple species: improving identification across recording conditions</a></li>\n<li><a href=\"https://www.pnas.org/content/115/25/E5716/\" target=\"_blank\">Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning</a></li>\n<li><a href=\"https://arxiv.org/abs/1912.10211\" target=\"_blank\">PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition</a></li>\n<li><a href=\"https://arxiv.org/abs/1904.08779\" target=\"_blank\">SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition</a></li>\n<li><a href=\"https://ai.googleblog.com/2019/04/specaugment-new-data-augmentation.html\" target=\"_blank\">SpecAugment Google AI Blog</a></li>\n<li><a href=\"https://arxiv.org/pdf/1710.09412.pdf\" target=\"_blank\">mixup: BEYOND EMPIRICAL RISK MINIMIZATION</a></li>\n</ul>\n<h1>Weak Label Learning:</h1>\n<ul>\n<li><a href=\"https://arxiv.org/pdf/1804.09288.pdf\" target=\"_blank\">A Closer Look at Weak Label Learning for Audio Events</a></li>\n</ul>\n<h1>Some benchmarks:</h1>\n<ul>\n<li><a href=\"https://arxiv.org/pdf/2010.10915.pdf\" target=\"_blank\">CONTRASTIVE LEARNING OF GENERAL-PURPOSE AUDIO REPRESENTATIONS (COLA)</a></li>\n</ul>",
      "rawMarkdown": "I am opening this thread for competition-related research papers and previous works, I will keep adding throughout the competition. \n\n# Audio Detection\n\n- [Automatic acoustic detection of birds through deep learning: the first Bird Audio Detection challenge](https://arxiv.org/abs/1807.05812)\n- [Automatic acoustic identification of individuals in multiple species: improving identification across recording conditions](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6505557/)\n- [Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning](https://www.pnas.org/content/115/25/E5716/)\n- [PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition](https://arxiv.org/abs/1912.10211)\n- [SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition](https://arxiv.org/abs/1904.08779)\n- [SpecAugment Google AI Blog](https://ai.googleblog.com/2019/04/specaugment-new-data-augmentation.html)\n- [mixup: BEYOND EMPIRICAL RISK MINIMIZATION](https://arxiv.org/pdf/1710.09412.pdf)\n\n# Weak Label Learning:\n- [A Closer Look at Weak Label Learning for Audio Events](https://arxiv.org/pdf/1804.09288.pdf)\n\n# Some benchmarks:\n- [CONTRASTIVE LEARNING OF GENERAL-PURPOSE AUDIO REPRESENTATIONS (COLA)](https://arxiv.org/pdf/2010.10915.pdf)",
      "votes": null
    },
    {
      "id": "1082399",
      "postDate": "11/17/2020 21:37:26",
      "content": "<p>My favorite audio classification articles:</p>\n<ul>\n<li><a href=\"https://arxiv.org/abs/1912.10211\" target=\"_blank\">PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition</a></li>\n<li><a href=\"http://ceur-ws.org/Vol-2380/paper_86.pdf\" target=\"_blank\">BirdCLEF 2019 winning solution</a></li>\n</ul>",
      "rawMarkdown": "My favorite audio classification articles:\n* [PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition](https://arxiv.org/abs/1912.10211)\n* [BirdCLEF 2019 winning solution](http://ceur-ws.org/Vol-2380/paper_86.pdf)",
      "votes": null
    },
    {
      "id": "1082433",
      "postDate": "11/17/2020 22:11:27",
      "content": "<ul>\n<li><a href=\"https://www.kaggle.com/c/birdsong-recognition/discussion/158933\" target=\"_blank\">Nice summary post with lots of links by</a> by <a href=\"https://www.kaggle.com/louise2001\" target=\"_blank\">@louise2001</a> </li>\n<li><a href=\"https://github.com/AgaMiko/bird-recognition-review\" target=\"_blank\">A long list of related resources by \nAgnieszka Mikołajczyk</a></li>\n</ul>",
      "rawMarkdown": "* [Nice summary post with lots of links by] (https://www.kaggle.com/c/birdsong-recognition/discussion/158933) by @louise2001 \n* [A long list of related resources by \nAgnieszka Mikołajczyk] (https://github.com/AgaMiko/bird-recognition-review)",
      "votes": null
    },
    {
      "id": "1111683",
      "postDate": "12/13/2020 23:11:12",
      "content": "<p>Hi <a href=\"https://www.kaggle.com/Ultron\" target=\"_blank\">@Ultron</a> thanks for \"Research Papers and Previous works Placeholder\". I look forward to you updating the list. Good start and well done.</p>",
      "rawMarkdown": "Hi @Ultron thanks for \"Research Papers and Previous works Placeholder\". I look forward to you updating the list. Good start and well done.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1082399,
      "author_name": "gaborfodor",
      "author_url": "",
      "post_date": "11/17/2020 21:37:26",
      "content": "<p>My favorite audio classification articles:</p>\n<ul>\n<li><a href=\"https://arxiv.org/abs/1912.10211\" target=\"_blank\">PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition</a></li>\n<li><a href=\"http://ceur-ws.org/Vol-2380/paper_86.pdf\" target=\"_blank\">BirdCLEF 2019 winning solution</a></li>\n</ul>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1082433,
      "author_name": "gaborfodor",
      "author_url": "",
      "post_date": "11/17/2020 22:11:27",
      "content": "<ul>\n<li><a href=\"https://www.kaggle.com/c/birdsong-recognition/discussion/158933\" target=\"_blank\">Nice summary post with lots of links by</a> by <a href=\"https://www.kaggle.com/louise2001\" target=\"_blank\">@louise2001</a> </li>\n<li><a href=\"https://github.com/AgaMiko/bird-recognition-review\" target=\"_blank\">A long list of related resources by \nAgnieszka Mikołajczyk</a></li>\n</ul>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1111683,
      "author_name": "puzuwe",
      "author_url": "",
      "post_date": "12/13/2020 23:11:12",
      "content": "<p>Hi <a href=\"https://www.kaggle.com/Ultron\" target=\"_blank\">@Ultron</a> thanks for \"Research Papers and Previous works Placeholder\". I look forward to you updating the list. Good start and well done.</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1082394": "I am opening this thread for competition-related research papers and previous works, I will keep adding throughout the competition. \n\n# Audio Detection\n\n- [Automatic acoustic detection of birds through deep learning: the first Bird Audio Detection challenge](https://arxiv.org/abs/1807.05812)\n- [Automatic acoustic identification of individuals in multiple species: improving identification across recording conditions](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6505557/)\n- [Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning](https://www.pnas.org/content/115/25/E5716/)\n- [PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition](https://arxiv.org/abs/1912.10211)\n- [SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition](https://arxiv.org/abs/1904.08779)\n- [SpecAugment Google AI Blog](https://ai.googleblog.com/2019/04/specaugment-new-data-augmentation.html)\n- [mixup: BEYOND EMPIRICAL RISK MINIMIZATION](https://arxiv.org/pdf/1710.09412.pdf)\n\n# Weak Label Learning:\n- [A Closer Look at Weak Label Learning for Audio Events](https://arxiv.org/pdf/1804.09288.pdf)\n\n# Some benchmarks:\n- [CONTRASTIVE LEARNING OF GENERAL-PURPOSE AUDIO REPRESENTATIONS (COLA)](https://arxiv.org/pdf/2010.10915.pdf)",
    "1082399": "My favorite audio classification articles:\n* [PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition](https://arxiv.org/abs/1912.10211)\n* [BirdCLEF 2019 winning solution](http://ceur-ws.org/Vol-2380/paper_86.pdf)",
    "1082433": "* [Nice summary post with lots of links by] (https://www.kaggle.com/c/birdsong-recognition/discussion/158933) by @louise2001 \n* [A long list of related resources by \nAgnieszka Mikołajczyk] (https://github.com/AgaMiko/bird-recognition-review)",
    "1111683": "Hi @Ultron thanks for \"Research Papers and Previous works Placeholder\". I look forward to you updating the list. Good start and well done."
  },
  "source": "meta"
}