Tacotron-2
train-procgen
| Tacotron-2 | train-procgen | |
|---|---|---|
| 1 | 1 | |
| 2,235 | 166 | |
| - | 0.0% | |
| 0.0 | 0.0 | |
| 10 months ago | about 1 year ago | |
| Python | Python | |
| MIT License | MIT License |
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Tacotron-2
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[D] How to Create a Fixed-Length, Binary, Sequence of Tokens Embedding?
This reminds me a lot of the problem of predicting an integer-valued output for an image or audio sequence, where you want to predict a value between 0 and 255, or even say 65536, but you want to help the model understand that the result is categorical, but some categories are closer to each other. I learned recently that one approach to this used in Tacotron 2 (speech synthesis) is called a Mixture of Logistics. There is a not very good blog post that goes over it, but links to a very in-depth explanation in a github issue of all places.. might be interesting for you.
train-procgen
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Procgen environments "easy" vs "hard" difficulty - what are they?
Found relevant code at https://github.com/openai/train-procgen + all code implementations here
What are some alternatives?
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
transferlearning - Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
aspeak - A simple text-to-speech client for Azure TTS API.
Paperless - Scan, index, and archive all of your paper documents
MimicMania - MimicMania is a web application that allows you to generate speech and clone voices using text-to-speech technology. With MimicMania, you can create custom voices in a variety of languages and use them for a range of applications, from voiceovers to chatbots.
gpt-2 - Code for the paper "Language Models are Unsupervised Multitask Learners"
tacotron - A TensorFlow implementation of Google's Tacotron speech synthesis with pre-trained model (unofficial)
qlib - Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
ALAE - [CVPR2020] Adversarial Latent Autoencoders