NeMo
tacotron2
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NeMo | tacotron2 | |
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29 | 28 | |
10,084 | 4,890 | |
7.1% | 1.2% | |
9.8 | 0.0 | |
2 days ago | 4 months ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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NeMo
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[P] Making a TTS voice, HK-47 from Kotor using Tortoise (Ideally WaveRNN)
I don't test WaveRNN but from the ones that I know the best that is open source is FastPitch. And it's easy to use, here is the tutorial for voice cloning.
- [N] Huggingface/nvidia release open source GPT-2B trained on 1.1T tokens
- [D] What is the best open source text to speech model?
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[D] JAX vs PyTorch in 2023
Nowadays... bigger repos like https://github.com/NVIDIA/NeMo are all pytorch, lots of work also published by Meta and Microsoft is all torch. I check new work on GitHub all the time and I haven't seen a Tensorflow repo in years except one.
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[D] What's stopping you from working on speech and voice?
- https://github.com/NVIDIA/NeMo
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Can I use PyTorch to build a fast capitalization recoverer?
Can’t you use the NeMo model and just strip the punctuation from the output again if you don’t want it? You can also fine tune the the model with capitalization only if you look at the examples https://github.com/NVIDIA/NeMo/blob/stable/tutorials/nlp/Punctuation_and_Capitalization.ipynb The capitalization and punctuation are annotated separately (U indicates that the word should be upper cased, and O - no capitalization ). The model seems to be a token level classifier not seq to seq so there should also be a way to get just the capitalization part but you would have to look into the model as it’s not shown in the examples.
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I made a free transcription service powered by Whisper AI
I think there's been talk to do speaker diarization with whisper-asr-webservice[0] which is also written in python and should be able to make use of goodies such as pyannote-audio, py-webrtcvad, etc.
Whisper is great but at the point we get to kludging various things together it starts to make more sense to use something like Nvidia NeMo[1] which was built with all of this in mind and more
[0] - https://github.com/ahmetoner/whisper-asr-webservice
[1] - https://github.com/NVIDIA/NeMo
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Mozilla Common Voice - Korean Language is live - Help Build a Korean Corpus for Training AI/Navi/etc
[커먼보이스 전자우편](mailto:[email protected]) || Common Voice || Korean Language Homepage || FAQs || Speaking Aloud and Reviewing Recordings || Sentence Collector || NVidia/NeMo
- Whisper – open source speech recognition by OpenAI
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Using Edge Biometrics For Better AI Security System Development
The final security grain was added with speech-to-text anti-spoofing built on QuartzNet from the Nemo framework. This model provides a decent quality user experience and is suitable for real-time scenarios. To measure how close what the person says to what the system expects, requires calculation of the Levenshtein distance between them.
tacotron2
- [D] What is the best open source text to speech model?
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[D] The model used in the AI generated Jay-z vocals
Which might use https://github.com/NVIDIA/tacotron2 in their backend
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Can anyone reccomend any free voice cloning software/websites even if it provided limited word options
One thing is uberduck.ai but I think it's freemium (it's free but some features are premium). There's also tacotron 2.0 and its pytorch page. Many other softwares on sub but tacotron gave this and this and this.
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Sauron be spitting bars
Maybe we can use AI to hear this rapped by a famous rapper?
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Kerfuś
Sadly GothicBot the TTS I knew, doesn't exist anymore, but here is an alternative. It works in polish from what I heard.
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How far are we from being able to clone a singers voice?
From what I’ve seen, NVIDIA’s Tacotron2 can already be used to create some pretty convincing singing.
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Is it possible to make compelling synthesized speech with fairly low-quality recordings?
You might want to try something like Tacotron 2 by Nvidia to experiment with your current data.
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What voice-changing apps are available right now?
We have the TorToiSe repo, the SV2TTS repo, and from here you have the other models like Tacotron 2, FastSpeech 2, and such. A there is a lot that goes into training a baseline for these models on the LJSpeech and LibriTTS datasets. Fine tuning is left up to the user.
- The OG (OC)
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XQC Falls for dono thinkng its Adept
I had tried tacotron2 + waveglow and it's quite easy to get very good results. The hardest part is collecting clean data.
What are some alternatives?
pyannote-audio - Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
tortoise-tts - A multi-voice TTS system trained with an emphasis on quality
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.
Voice-Cloning-App - A Python/Pytorch app for easily synthesising human voices
whisper - Robust Speech Recognition via Large-Scale Weak Supervision
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
espnet - End-to-End Speech Processing Toolkit
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
waveglow - A Flow-based Generative Network for Speech Synthesis
larynx - End to end text to speech system using gruut and onnx