/Text-to-Audio-with-Bark

Exploring Bark, the Open-Source Text-to-Audio Generative Model

Primary LanguageJupyter NotebookMIT LicenseMIT

Exploring Text-to-Audio with Bark

Link to article: https://betterprogramming.pub/text-to-audio-generation-with-bark-clearly-explained-4ee300a3713a

Context

  • Amidst the transformative surge of generative AI, text-to-audio models are emerging as one of the most promising frontiers.
  • These advances are not just about converting text to speech, but also about crafting audio experiences that are indistinguishable from human-produced content.
  • From audiobooks narrated in any voice imaginable to dynamic music compositions prompted by mere sentences, the potential applications are vast and captivating.
  • In this article, we delve into the capabilities and technical intricacies of Bark, an open-source text-prompted audio generation model in Python.

Introducing Bark

Bark is a transformer-based text-to-audio model capable of generating realistic multilingual speech, music, and sound effects. It is created by Suno, a research-driven company that develops cutting-edge audio AI. As Bark was developed for research purposes, its pre-trained model checkpoints have been made open-source and available for commercial use, which is a valuable contribution to the generative AI community.


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