whisperspeech-small

Maintainer: lucataco

Total Score

1

Last updated 6/19/2024
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Model Overview

whisperspeech-small is an open-source text-to-speech system built by inverting the Whisper speech recognition model. It was developed by lucataco, a contributor at Replicate. This model can be used to generate audio from text, allowing users to create their own text-to-speech applications.

whisperspeech-small is similar to other open-source text-to-speech models like whisper-diarization, whisperx, and voicecraft, which leverage the capabilities of the Whisper speech recognition model in different ways.

Model Inputs and Outputs

whisperspeech-small takes a text prompt as input and generates an audio file as output. The model can handle various languages, and users can optionally provide a speaker audio file for zero-shot voice cloning.

Inputs

  • Prompt: The text to be synthesized into speech
  • Speaker: URL of an audio file for zero-shot voice cloning (optional)
  • Language: The language of the text to be synthesized

Outputs

  • Audio File: The generated speech audio file

Capabilities

whisperspeech-small can generate high-quality speech audio from text in a variety of languages. The model uses the Whisper speech recognition architecture to generate the audio, which results in natural-sounding speech. The zero-shot voice cloning feature also allows users to customize the voice used for the synthesized speech.

What Can I Use It For?

whisperspeech-small can be used to create text-to-speech applications, such as audiobook narration, language learning tools, or accessibility features for websites and applications. The model's ability to generate speech in multiple languages makes it useful for international or multilingual projects. Additionally, the zero-shot voice cloning feature allows for more personalized or branded text-to-speech outputs.

Things to Try

One interesting thing to try with whisperspeech-small is using the zero-shot voice cloning feature to generate speech that matches the voice of a specific person or character. This could be useful for creating audiobooks, podcasts, or interactive voice experiences. Another idea is to experiment with different text prompts and language settings to see how the model handles a variety of input content.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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