I will include here various resources for Birdcall Identification
\n\nJoly, A., Goëau, H., Botella, C., Kahl, S., Poupard, M., Servajean, M., … & Schlüter, J. (2019). LifeCLEF 2019: Biodiversity Identification and Prediction Challenges. In European Conference on Information Retrieval (pp. 275-282).
\n\nI will include here various resources for Birdcall Identification
\n\nJoly, A., Goëau, H., Botella, C., Kahl, S., Poupard, M., Servajean, M., … & Schlüter, J. (2019). LifeCLEF 2019: Biodiversity Identification and Prediction Challenges. In European Conference on Information Retrieval (pp. 275-282).
\n\nI tried this early on, and the results for some audios are great, but it's slow/time consuming. Also it still leaves one with the challenge of identifying which of the channels actually contains the right portion. Do you have any thoughts/recommendations in that regard?
", "rawMarkdown": "I tried this early on, and the results for some audios are great, but it's slow/time consuming. Also it still leaves one with the challenge of identifying which of the channels actually contains the right portion. Do you have any thoughts/recommendations in that regard?", "votes": null }, { "id": "907194", "postDate": "06/29/2020 18:44:24", "content": "Thanks Gabriel! I added this page to my own literature review discussion thread - https://www.kaggle.com/c/birdsong-recognition/discussion/162688 .
", "rawMarkdown": "Thanks Gabriel! I added this page to my own literature review discussion thread - https://www.kaggle.com/c/birdsong-recognition/discussion/162688 .", "votes": null }, { "id": "915114", "postDate": "07/04/2020 13:34:35", "content": "I thought about this mostly as one possible option for the pre-processing of the signals.
", "rawMarkdown": "I thought about this mostly as one possible option for the pre-processing of the signals.", "votes": null }, { "id": "915118", "postDate": "07/04/2020 13:36:06", "content": "Thank you for the link. Indeed, you selected some very useful materials.
", "rawMarkdown": "Thank you for the link. Indeed, you selected some very useful materials.", "votes": null } ], "comments": [ { "id": 906629, "author_name": "roman99", "author_url": "", "post_date": "06/29/2020 13:03:44", "content": "I tried this early on, and the results for some audios are great, but it's slow/time consuming. Also it still leaves one with the challenge of identifying which of the channels actually contains the right portion. Do you have any thoughts/recommendations in that regard?
", "votes": null, "replies": [ { "id": 915114, "author_name": "gpreda", "author_url": "", "post_date": "07/04/2020 13:34:35", "content": "I thought about this mostly as one possible option for the pre-processing of the signals.
", "votes": null, "replies": [] } ] }, { "id": 907194, "author_name": "tpmeli", "author_url": "", "post_date": "06/29/2020 18:44:24", "content": "Thanks Gabriel! I added this page to my own literature review discussion thread - https://www.kaggle.com/c/birdsong-recognition/discussion/162688 .
", "votes": null, "replies": [ { "id": 915118, "author_name": "gpreda", "author_url": "", "post_date": "07/04/2020 13:36:06", "content": "Thank you for the link. Indeed, you selected some very useful materials.
", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "895390": "I will include here various resources for Birdcall Identification\n\n## Audio signals separation\n\n* Cocktail Party problem algorithms: [Algorithms for Source Separation - with Cocktail Party Applications](http://www2.imm.dtu.dk/pubdb/edoc/imm5270.pdf) \n* Cocktail Party problem solutions: [cocktail party algorithm SVD implementation … in one line of code?](https://stackoverflow.com/questions/20414667/cocktail-party-algorithm-svd-implementation-in-one-line-of-code) \n* Sklearn implementation for FastICA: [sklearn.decomposition.FastICA](https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.FastICA.html) \n* Example of using FastICA: [Blind source separation using FastICA](https://scikit-learn.org/stable/auto_examples/decomposition/plot_ica_blind_source_separation.html) \n* Akarsh Kumar, [Audio Source Separation with Deep Learning](https://towardsdatascience.com/audio-source-separation-with-deep-learning-e7250e8926f7) \n* Carstein Klein, [Separating mixed signals with Independent Component Analysis](https://towardsdatascience.com/separating-mixed-signals-with-independent-component-analysis-38205188f2f4) \n* Ethan Manilow, Prem Seetharaman and Bryan Pardo, [Flexible easy-to-use audio source separation](https://github.com/nussl/nussl)\n\n## Literature & solutions reviews\n\n* Agnieszka Mikołajczyk, [Bird recognition - review of useful resources](https://github.com/AgaMiko/bird-recognition-review) \n* Agnieszka Mikołajczyk, [Data Augmentation Review](https://github.com/AgaMiko/data-augmentation-review) \n* Kahl, S., Wilhelm-Stein, T., Klinck, H., Kowerko, D., & Eibl, M. (2018). [A Baseline for Large-Scale Bird Species Identification in Field Recordings](http://ceur-ws.org/Vol-2125/paper_85.pdf). In CLEF 2018 (Working Notes) \n* Stefan Kahl, [Identifying Birds by Sound: Large-scale Acoustic Event Recognition for Avian Activity Monitoring](https://monarch.qucosa.de/api/qucosa%3A36986/attachment/ATT-0/) \n* Joly, A., Goëau, H., Botella, C., Kahl, S., Poupard, M., Servajean, M., … & Schlüter, J. (2019). [LifeCLEF 2019: Biodiversity Identification and Prediction Challenges](https://www.researchgate.net/profile/Henning_Mueller2/publication/331733244_LifeCLEF_2019_Biodiversity_Identification_and_Prediction_Challenges/links/5c8a35e592851c1df9407d46/LifeCLEF-2019-Biodiversity-Identification-and-Prediction-Challenges.pdf). In European Conference on Information Retrieval (pp. 275-282).\n## Trivia \n\n* [Shazam for Birds: Three Apps That Recognize Bird Calls](https://lifehacker.com/shazam-for-birds-three-apps-that-recognize-bird-calls-1797955537)", "906629": "I tried this early on, and the results for some audios are great, but it's slow/time consuming. Also it still leaves one with the challenge of identifying which of the channels actually contains the right portion. Do you have any thoughts/recommendations in that regard?", "907194": "Thanks Gabriel! I added this page to my own literature review discussion thread - https://www.kaggle.com/c/birdsong-recognition/discussion/162688 .", "915114": "I thought about this mostly as one possible option for the pre-processing of the signals.", "915118": "Thank you for the link. Indeed, you selected some very useful materials." }, "source": "meta" }