superduperdb
tortoise-tts
superduperdb | tortoise-tts | |
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24 | 145 | |
4,390 | 11,881 | |
3.2% | - | |
9.9 | 8.0 | |
5 days ago | 12 days ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
superduperdb
- FLaNK Stack Weekly 12 February 2024
- FLaNK Stack Weekly 11 Dec 2023
- Trending on GitHub top 10 globally for the 4th day in a row: Open-source framework for integrating OpenAI with major databases
- Trending on GitHub top 10 for the 4th day in a row: Open-source framework for integrating AI models and APIs directly with all major SQL databases
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Trending on GitHub top 10 for the 4th day in a row and official technology partner of MongoDB: Open-source framework for integrating AI with MongoDB and MongoDB Atlas
Definitely check it out: https://github.com/SuperDuperDB/superduperdb and find it here: https://cloud.mongodb.com/ecosystem/
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Trending on GitHub top 10 globally for the 4th day in a row: Open-source framework for integrating OpenAI and GPT with major databases
Build a chatbot with OpenAI: https://github.com/SuperDuperDB/superduperdb/blob/main/examples/question_the_docs.ipynb
- SuperDuperDB - how to use it to talk to your documents locally using llama 7B or Mistral 7B?
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Trending on GitHub globally 3 days in a row: SuperDuperDB, a framework for integrating AI with major databases (making them super-duper)
It is for building AI (into your) apps easily without complex pipelines and make your database intelligent (including vector search), definitely check it out: https://github.com/SuperDuperDB/superduperdb
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🔮 SuperDuperDB is #3 on GitHub Trending globally! 🥉
VentureBeat already covered the launch This is our website This is our main GitHub repository
tortoise-tts
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ESpeak-ng: speech synthesizer with more than one hundred languages and accents
The quality also depends on the type of model. I'm not really sure what ESpeak-ng actually uses? The classical TTS approaches often use some statistical model (e.g. HMM) + some vocoder. You can get to intelligible speech pretty easily but the quality is bad (w.r.t. how natural it sounds).
There are better open source TTS models. E.g. check https://github.com/neonbjb/tortoise-tts or https://github.com/NVIDIA/tacotron2. Or here for more: https://www.reddit.com/r/MachineLearning/comments/12kjof5/d_...
- FLaNK Stack Weekly 12 February 2024
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OpenVoice: Versatile Instant Voice Cloning
I use Tortoise TTS. It's slow, a little clunky, and sometimes the output gets downright weird. But it's the best quality-oriented TTS I've found that I can run locally.
https://github.com/neonbjb/tortoise-tts
- [discussion] text to voice generation for textbooks
- DALL-E 3: Improving image generation with better captions [pdf]
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Open Source Libraries
neonbjb/tortoise-tts
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Running Tortoise-TTS - IndexError: List out of range
EDIT: It appears to be the exact same issue as this
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My Deep Learning Rig
It was primarily being used to train TTS models (see https://github.com/neonbjb/tortoise-tts), which largely fit into a single GPUs memory. So, for data parallelism, x8 PCIe isn't that much of a concern.
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PlayHT2.0: State-of-the-Art Generative Voice AI Model for Conversational Speech
Previously TortoiseTTS was associated with PlayHT in some way, although the exact connection is a bit vague [0].
From the descriptions here it sounds a lot like AudioLM / SPEAR TTS / some of Meta's recent multilingual TTS approaches, although those models are not open source, sounds like PlayHT's approach is in a similar spirit. The discussion of "mel tokens" is closer to what I would call the classic TTS pipeline in many ways... PlayHT has generally been kind of closed about what they used, would be interesting to know more.
I assume the key factor here is high quality, emotive audio with good data cleaning processes. Probably not even a lot of data, at least in the scale of "a lot" in speech, e.g. ASR (millions of hours) or TTS (hundreds to thousands). As opposed to some radically new architectural piece never before seen in the literature, there are lots of really nice tools for emotive and expressive TTS buried in recent years of publications.
Tacotron 2 is perfectly capable of this type of stuff as well, as shown by Dessa [1] a few years ago (this writeup is a nice intro to TTS concepts). With the limit largely being, at some point you haven't heard certain phonetic sounds before in a voice, and need to do something to get plausible outcomes for new voices.
[0] Discussion here https://github.com/neonbjb/tortoise-tts/issues/182#issuecomm...
[1] https://medium.com/dessa-news/realtalk-how-it-works-94c1afda...
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Comparing Tortoise and Bark for Voice Synthesis
Tortoise GitHub repo - Source code, documentation, and usage guide
What are some alternatives?
ds2 - Easiest way to use AI models without coding (Web UI & API support)
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
bark - 🔊 Text-Prompted Generative Audio Model
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
nyc_traffic_flask - Flask App with leaflet.js that can perform NYC Traffic Prediction
piper - A fast, local neural text to speech system
Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials - A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
tacotron2 - Tacotron 2 - PyTorch implementation with faster-than-realtime inference
mlops-python-package - Kickstart your MLOps initiative with a flexible, robust, and productive Python package.
larynx - End to end text to speech system using gruut and onnx