bark
tortoise-tts
bark | tortoise-tts | |
---|---|---|
67 | 145 | |
33,383 | 12,193 | |
2.6% | - | |
4.7 | 7.7 | |
7 days ago | about 1 month ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | Apache License 2.0 |
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bark
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Exploring Bark, the Open Source Text-to-Speech Model
!pip install git+https://github.com/suno-ai/bark.git
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AI-generated sad girl with piano performs the text of the MIT License
To my knowledge, the model being used for this is "chirp" which is 'based on' bark[1], an AI text to speech model.
The github page for bark links to a page about chirp, which returns a 404 page for me [2]. that the model for suno.ai's song generator isn't too much different than the text to speech model.
My hunch is that it was something like a coincidence that the bark model was capable of producing music, and that was spun off into this product. Unfortunately, there seems to still be issues with bark when generating long (like book length) spoken audio. Which is too bad, as someone who's worked jobs that require lots of driving, it would be awesome to be able to have any text read to me in a natural sounding voice.
[1]https://github.com/suno-ai/bark
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Generating music in the waveform domain (2020)
Stable-audio and MusicGen sounds better than Jukebox.
But the best so far is Suno.ai ( https://app.suno.ai ) especially with their V3 model they have very impressive results, the fidelity is not studio quality but they're getting very close.
It's very likely based on their TTS model they have released before Bark, but trained on more data and with higher resolution.
https://github.com/suno-ai/bark
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Stable-Audio-Demo
https://github.com/suno-ai/bark
> Bark was developed for research purposes. It is not a conventional text-to-speech model but instead a fully generative text-to-audio model, which can deviate in unexpected ways from provided prompts. Suno does not take responsibility for any output generated. Use at your own risk, and please act responsibly.
I've generated probably >200 songs now with Suno, of which perhaps 10 have been any good, and I can't detect any pattern in terms of the outputs.
Here's another one which is pretty good. I accidentally copied and pasted the prompt and lyrics, and it's amazing to me how 'musically' it renders the prompt:
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Suno AI
hahah wow! cool :-)
PS: OT, I am reading this Bark thing(https://github.com/suno-ai/bark). Can I run it locally on a Macbook 2015 with 8GB RAM?
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SDXL + SVD + Suno AI
I have it locally. The model is on huggingface. It runs with about 8GB VRAM.
- [discussion] text to voice generation for textbooks
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Open Source Libraries
suno-ai/bark
- Weird A.I. Yankovic, a cursed deep dive into the world of voice cloning
- FLaNK Stack Weekly 2 October 2023
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?
SadTalker - [CVPR 2023] SadTalker:Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
whisper.cpp - Port of OpenAI's Whisper model in C/C++
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
Retrieval-based-Voice-Conversion-WebUI - Easily train a good VC model with voice data <= 10 mins!
piper - A fast, local neural text to speech system
tacotron2 - Tacotron 2 - PyTorch implementation with faster-than-realtime inference
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
larynx - End to end text to speech system using gruut and onnx
audiolm-pytorch - Implementation of AudioLM, a SOTA Language Modeling Approach to Audio Generation out of Google Research, in Pytorch
TensorFlowTTS - :stuck_out_tongue_closed_eyes: TensorFlowTTS: Real-Time State-of-the-art Speech Synthesis for Tensorflow 2 (supported including English, French, Korean, Chinese, German and Easy to adapt for other languages)