vocode-python
tortoise-tts
vocode-python | tortoise-tts | |
---|---|---|
9 | 145 | |
2,368 | 11,944 | |
6.4% | - | |
9.1 | 8.0 | |
7 days ago | 2 days ago | |
Python | Jupyter Notebook | |
MIT License | 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.
vocode-python
- Launch HN: Retell AI (YC W24) – Conversational Speech API for Your LLM
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Ask HN: Who is hiring? (February 2024)
Vocode || Engineering (multiple roles) || SF/Remote || Full-time/Contract || https://vocode.dev
- Show HN: WhisperFusion – Ultra-low latency conversations with an AI chatbot
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April 2023
Vocode–an open source library for building LLM applications you can talk to. (https://github.com/vocodedev/vocode-python)
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Serverless voice chat with Vicuna-13B
Coqui also looks interesting.
https://github.com/coqui-ai/TTS
Support for it was recently added to vocode:
https://github.com/vocodedev/vocode-python/pull/56
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Vocode is an open source library that makes it easy to build voice-based LLM apps
Direct link to the code: https://github.com/vocodedev/vocode-python
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Show HN: Vocode (YC W23) Is Back with an April Fools Special – PrankGPT
Hey everyone! We are so grateful for the warm reception from our launch this week.
We're back with PrankGPT (origin story of Vocode), rebuilt using our library https://github.com/vocodedev/vocode-python
Source code for the backend is public and available on replit to check it out
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Show HN: YakGPT – A locally running, hands-free ChatGPT UI
Given that Vocode (realtime audio, llm, etc) came out a few days ago, could you speak to how yours compares to it?
https://github.com/vocodedev/vocode-python
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Gen Z GPT hotline demo
It's a demo for their new open source library integrating several AI tools: https://github.com/vocodedev/vocode-python
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?
bark - 🔊 Text-Prompted Generative Audio Model
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
Flowise - Drag & drop UI to build your customized LLM flow
PentestGPT - A GPT-empowered penetration testing tool
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
ChatGPT-Next-Web - A cross-platform ChatGPT/Gemini UI (Web / PWA / Linux / Win / MacOS). 一键拥有你自己的跨平台 ChatGPT/Gemini 应用。
piper - A fast, local neural text to speech system
textSQL
tacotron2 - Tacotron 2 - PyTorch implementation with faster-than-realtime inference
prompt-engineering - ChatGPT Prompt Engineering for Developers - deeplearning.ai
larynx - End to end text to speech system using gruut and onnx