by collinc777 on 1/22/24, 9:16 PM with 0 comments
I’ve explored text-to-speech (TTS) for articles using tools like Speechify. However, I noticed a gap: TTS lacked the engagement I found in podcasts. I think there’s two reasons why:
1. Articles are visually oriented, while podcasts are audio-centric. 2. The personal connection we develop with our favorite podcasters.
Addressing this, a-to-p leverages AI to bridge the gap. The idea is to morph articles into a format resembling podcast transcripts before applying TTS. This approach, in my experience, significantly enhances engagement compared to standard TTS.
The roadmap for a-to-p includes:
- Tackling the content and length alterations in the transformation process. - Implementing open-source LLMs for generating transcripts. - Integrating high-quality, affordable open-source TTS models. - Adding Intro and Outro segments for a complete podcast experience.
I’m eager for any feedback or contributions to the project. Your insights can greatly shape a-to-p’s future!