Thousands of bird sounds, visualized using machine learning.
Bird sounds vary widely. This experiment uses machine learning to organize thousands of bird sounds. The computer wasn’t given tags or the birds’ names – only the audio. Using a technique called t-SNE, the computer created this map, where similar sounds are placed closer together.
https://aiexperiments.withgoogle.com/bird-sounds
This is not an official Google product.
Built by Kyle McDonald, Manny Tan, Yotam Mann, and friends at Google Creative Lab. Thanks to Cornell Lab of Ornithology for their support. The Essential Set for North America sounds are provided by the Macaulay Library. Check out more at [A.I. Experiments] (https://aiexperiments.withgoogle.com).
To build the client-side javascript, first install node and webpack. Then you can install of the dependencies and build the files by typing the following in the terminal:
npm install
webpack -pTo generate a t-SNE with your own audio, check out this repository from Kyle McDonald and the Infinite Drum Machine, which shares a lot of the same techniques.
Third party directories may have different (non-Apache 2.0) licenses.
Copyright 2016 Google Inc. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.