Weird A.I. Yankovic, a cursed deep dive into the world of voice cloning

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  1. bark

    🔊 Text-Prompted Generative Audio Model

  2. InfluxDB

    InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.

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  3. silero-models

    Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple

    I doubt it's currently actually "the best open source text to speech", but the answer I came up with when throwing a couple of hours at the problem some months ago was "Silero" [0, 1].

    Following the "standalone" guide [2], it was pretty trivial to make the model render my sample text in about 100 English "voices" (many of which were similar to each other, and in varying quality). Sampling those, I got about 10 that were pretty "good". And maybe 6 that were the "best ones" (pretty natural, not annoying to listen to).

    IIRC the license was free for noncommercial use only. I'm not sure exactly "how open source" they are, but it was simple to install the dependencies and write the basic Python to try it out; I had to write a for loop to try all the voices like I wanted. I ended using something else for the project for other reasons, but this could still be fairly good backup option for some use cases IMO.

      [0] https://github.com/snakers4/silero-models#text-to-speech

  4. piper

    A fast, local neural text to speech system

    > What's the best open source text to speech?

    I haven't re-evaluated OSS TTS options for a few months but from my own experience earlier in the year I've been pleased with the results I've gotten from Piper:

    * https://github.com/rhasspy/piper

    I've primarily used it with the LibriTTS-based voices due to their license but if it's for personal local use you can probably use some of the other even higher quality voices.

    The official samples are here: https://rhasspy.github.io/piper-samples/

    Here's a small number of pre-rendered samples I've used that were generated from a WIP Piper port of my Dialogue Tool[0] project: https://rancidbacon.gitlab.io/piper-tts-demos/

    While it's not perfect & output quality varies for a number of reasons, I've been using it because it's MIT licensed & there's multiple diverse voice options with licenses that suit my purposes.

    (Piper and its predecessors Larynx & Mimic3 are significantly ahead of where other FLOSS options had been up until their existence in terms of quality.)

    [0] https://rancidbacon.itch.io/dialogue-tool-for-larynx-text-to...

  5. StyleTTS2

    StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models

    You're in luck, the code dropped 6 hours ago :) https://github.com/yl4579/StyleTTS2

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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