SoundNet: Learning Sound Representations from Unlabeled Video. NIPS 2016
Learn about sound by analyzing audio from videos without needing labeled data.
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Free · no card · unsubscribe anytimeSoundNet: Learning Sound Representations from Unlabeled Video. NIPS 2016
soundnet has 466 stars on GitHub. It has been forked 94 times. soundnet is written mainly in Lua. It has been in active development since 2016. soundnet is available under the MIT license. Its main topics are computer-vision, deep-learning, sound.
SoundNet: Learning Sound Representations from Unlabeled Video. NIPS 2016
soundnet is an open-source project. It is released under the MIT license.
Yes. soundnet is free and open source — you can use, modify and self-host it.
soundnet is available under the MIT license.
soundnet is written mainly in Lua.
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