basic-pitch
tortoise-tts
basic-pitch | tortoise-tts | |
---|---|---|
8 | 145 | |
2,941 | 11,819 | |
2.9% | - | |
8.4 | 8.0 | |
4 days ago | 4 days ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | Apache License 2.0 |
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basic-pitch
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Open Source Libraries
spotify/basic-pitch: Audio to midi converter
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Mac users: is it best to just rent a linux server?
I did just get it to work setting an alias for Python pointing to 3.11 but ran into this issue: https://github.com/spotify/basic-pitch/issues/63
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Transcribing music from audio?
There's https://github.com/spotify/basic-pitch, a free converter, but require CLI usage.
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Recommended python library for converting audio file into midi ?
Might be worthwhile checking out Spotify’s basic pitch library.
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How to make a sub bass follow a bit from a mudpie?
quick add on: definitely take a look at this https://github.com/spotify/basic-pitch its a much much better offline pitch detection algo that you could use to get the midi for your mudpie. I'd probably bounce a low passed copy at around 150-200Hz, making sure its completley mono and then feed that wav/aiff file to that pitch detector
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Spotify Research Open-Sources ‘Basic Pitch’: A Machine Learning Tool For Converting Audio Into MIDI
Continue reading | Check out the paper, github, project and post
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Spotify Introduces an Open-Source Tool to Fix a Big Problem for Modern Musicians - It's FOSS News
GitHub link
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?
ai-music - A vanilla Trasformer Decoder music generation model trained on Final Fantasy OST MIDI songs
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
THIRTY-DOLLAR-HAIRCUT-GENERATOR - 30 dollar haircut website MIDI converter - Using MIDIs, QUICKLY generate a chart for the "DON'T YOU LECTURE ME WITH YOUR THIRTY DOLLAR HAIRCUT" website. The site's by GDcolon, if you need to search it up.
bark - 🔊 Text-Prompted Generative Audio Model
gitpod - The developer platform for on-demand cloud development environments to create software faster and more securely.
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
concordia - Crowdsourcing platform for full text transcription and tagging. https://crowd.loc.gov
piper - A fast, local neural text to speech system
PiDTLN - Apply machine learning model DTLN for noise suppression and acoustic echo cancellation on Raspberry Pi
tacotron2 - Tacotron 2 - PyTorch implementation with faster-than-realtime inference
torchlambda - Lightweight tool to deploy PyTorch models to AWS Lambda
larynx - End to end text to speech system using gruut and onnx