spokestack-python
silero-models
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spokestack-python | silero-models | |
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7 | 32 | |
132 | 4,534 | |
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3.3 | 4.7 | |
over 2 years ago | 6 months ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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spokestack-python
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We're making it super easy to use voice in Python, and we want your feedback!
Our AutoML service will let you [redacted because we're not ready to say it publicly yet], using your own voice. Combining [redacted] with existing open-source SDK libraries & tutorials for [Python](https://github.com/spokestack/spokestack-python) allows you to utilize cutting-edge personalized voice technology.
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Sunday Daily Thread: What's everyone working on this week?
I’ve been working on this project for a while now. I’m really interested to discover if other developers want to add voice to their python projects.
I’ll be working on integrating spokestack into home-assistant
- Spokestack: Python Library for Voice Applications
- Spokestack: Embedded Voice Library for Python
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I love home assistant and I work on TTS in my day job. Should I do an add-on or an integration?
Ok so that’s my main concern. It seems like for distribution an integration is the way to go. Library is this for better context.
- Python Embedded Voice Library
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?
picovoice - On-device voice assistant platform powered by deep learning
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
Porcupine - On-device wake word detection powered by deep learning
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
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.
Caffe2
piper - A fast, local neural text to speech system
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
neptune-client - 📘 The MLOps stack component for experiment tracking