Serpent.AI
silero-models
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Serpent.AI | silero-models | |
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5 | 32 | |
6,321 | 4,546 | |
- | - | |
0.0 | 4.7 | |
over 2 years ago | 6 months ago | |
Python | Jupyter Notebook | |
MIT License | GNU General Public License v3.0 or later |
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Serpent.AI
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I forced an AI to watch 5000 Isaac episodes and this is what happened
A: I am. While serpent.ai attempted to get an AI to play Isaac, the project hasn't been updated in years.
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A bot is livestreaming. Clearly Blizzard doesn't care.
You don't need a whole team nowadays. Amazon has services that let you train your own neural nets with a little bit of knowledge. Then there are tools like SerpentAI that let your AI interface with games (don't know if it works with Blizzard games, but it works with Steam).
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I'm on a 64 bit win10 pc and want to make a tas for a unity game, that is what I have. How do I make a tas
i cant. is there any way https://github.com/SerpentAI/SerpentAI would work. the game is entirely mouse movements.
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Using NEAT and Serpent.AI to train an agent to play DK Country- is this a bad idea?
Hey! So, I'd like to implement NEAT machine learning to train an agent to play Donkey Kong Country, but there doesn't seem to be much in the way of tutorials/examples for Serpent.AI (like, its weirdly dead given how powerful it seems to be and github page is full of dead links) so I wanted to see if any of you fine folk would recommend for/against its use or that of an alternative. Any other advice also appreciated.
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Best Websites Every Programmer Should Visit
Serpent AI : Game Agent Framework. Helping you create AIs / Bots to play any game you own! BETA
silero-models
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Weird A.I. Yankovic, a cursed deep dive into the world of voice cloning
I doubt it's currently actually "the best open source text to speech", but the answer I came up with when throwing a couple of hours at the problem some months ago was "Silero" [0, 1].
Following the "standalone" guide [2], it was pretty trivial to make the model render my sample text in about 100 English "voices" (many of which were similar to each other, and in varying quality). Sampling those, I got about 10 that were pretty "good". And maybe 6 that were the "best ones" (pretty natural, not annoying to listen to).
IIRC the license was free for noncommercial use only. I'm not sure exactly "how open source" they are, but it was simple to install the dependencies and write the basic Python to try it out; I had to write a for loop to try all the voices like I wanted. I ended using something else for the project for other reasons, but this could still be fairly good backup option for some use cases IMO.
[0] https://github.com/snakers4/silero-models#text-to-speech
- What's the best text-to-speech free non-cloud software?
- Hey can anyone else add the text to speech
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Messing around with a TTS extension
Glados was the first experiment. I moved on to silero afterwards: https://github.com/snakers4/silero-models
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Ask HN: Open-source video transcribing software?
Some months ago I tried the Silero Models: https://github.com/snakers4/silero-models
With the audio sources I had, in English, the transcription had many mistakes. The good side is that installing and running the software worked as described in their documentation, so maybe it’s worth giving it a try by yourself.
- Silero V3:20种语言的快速高质量文本到语音,有173种声音 (Silero V3: fast high-quality text-to-speech in 20 languages with 173 voices)
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Hacker News top posts: Jun 20, 2022
Silero V3: fast high-quality text-to-speech in 20 languages with 173 voices\ (56 comments)
- Silero V3: fast high-quality text-to-speech in 20 languages with 173 voices
What are some alternatives?
Caffe2
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
Porcupine - On-device wake word detection powered by deep learning
DeepSpeech - DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
piper - A fast, local neural text to speech system
Projects - :page_with_curl: A list of practical projects that anyone can solve in any programming language.
Caffe - Caffe: a fast open framework for deep learning.