encodec
bark
encodec | bark | |
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18 | 9 | |
3,185 | 959 | |
2.0% | - | |
3.9 | 8.7 | |
4 months ago | 7 months ago | |
Python | Jupyter Notebook | |
MIT License | MIT License |
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encodec
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TSAC: Low Bitrate Audio Compression
Since Ballard's codec is "AI" based, can you add google's lyrav2 ( https://github.com/google/lyra ) and Facebook's/meta EnCodec ( https://github.com/facebookresearch/encodec ).
Also I don't seem to be able to access your page, so there might be error.
Finally, when doing opus comparison it's good now to denote if it is using Lace or NoLace decoder post processing filters that became available in opus 1.5 (note, this feature need to be enabled at compile time, and defying decode a new API call needs to be made to force higher complexity decoder) . See https://opus-codec.org/demo/opus-1.5/
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[R] Neural network for audio training sample size
But models rarely work on raw audio. You can also check EnCodec (https://github.com/facebookresearch/encodec) or SoundStream.
- Bark: A transformer based text to audio system
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[D]: Is voice cloning or natural TTS (like Elevenlabs) possible due to LLMs?
VALL-E from Microsoft is transformer over Encodec code. SPEAR-TTS from Google is basically AudioLM for TTS.
- Why hasn't Meta made LLaMA open source?
- ML Codecs Similar to Encodec by Facebook?
- Wie Österreich die Glasfaser verschlief - ORF Topos
- EnCodec: State-of-the-art deep learning based audio codec
- High Fidelity Neural Audio Compression
- EnCodec: High Fidelity Neural Audio Compression
bark
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To Bridge the Gap Until the Official Audiobooks Are Released I Tried Making a Myne TTS [P5V5]
So I looked around and decided to use Bark Infinity. (Originally wanted to use Amazon Polly, but don't have a credit card) I tried around and found out that the female storyteller voice sounds quite decently. So I used that and a reference clip of Myne's voice as prompt (which I think might have helped a little... I don't get all that program's features) to generate a whole chapter. That worked quite well.
- Free/Affordable Text to Speech AI?
- Local and open-source equivalent to HeyGen Text-to-Speech (TTS) AI?
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Whispers of Frostcliff Lodge
AI-generated voice. I'll have to try Bark Infinity and Speechify.
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Bark: A transformer based text to audio system
I'll link my Bark fork with long audio generation and other features on the root thread, I suppose: https://github.com/JonathanFly/bark
There's going to be a big update this week with some new stuff I haven't talked about. And a bunch of amazing, clear voices, with a huge variety of styles, that blow the default Suno voices out of the water.
Don't get too attached though. I was just playing around and made a Bark fork and it got more popular than expected. But I wasn't thinking about the hours of unpaid support and maintenance in my future that I definitely can NOT afford, for software I don't even really have a personal use case for. I'm not generating my own audiobooks or anything, I won’t be using it long term myself, I was just curious what Bark could do. (Turns out a LOT more than you might think at first glance, as you'll see this week.) So I'm trying to work out how I can elegantly wind this down and transition people somewhere else. But I'll keep it updated for at least a little while.
- Converting a Subreddit into a Podcast with GPT-4
- Ask a Text-To-Speech AI (Bark) to say "Why was six afraid of seven?" but ignore the "I'm done" token and force it to just keep talking.
- [R] 🐶 Bark - Text2Speech...But with Custom Voice Cloning using your own audio/text samples 🎙️📝
What are some alternatives?
bark - 🔊 Text-Prompted Generative Audio Model
bark-with-voice-clone - 🔊 Text-prompted Generative Audio Model - With the ability to clone voices
audiolm-pytorch - Implementation of AudioLM, a SOTA Language Modeling Approach to Audio Generation out of Google Research, in Pytorch
crowdcast - Converts a subreddit into a podcast
TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple