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Built a small prototype using #GPT3 - every app working with text should make language styling as accessible as text formatting. This improves accessibility for non-native speakers like myself, and allows to focus on the content while generating auxiliary data like subject etc.
199,341 просмотров • 3 лет назад •via X (Twitter)
Комментарии: 10
Looks like there’re open source GPT alternatives, too!
Awesome! Gonna be linking to this tomorrow in my newsletter!
Thanks Pete! Would love to see more people tinkering with these ideas 🙏
We did something very similar in @boodotai recently- need to post a vid
Really cool idea
This is hilariously fantastic! Like I’m five -> like they’re five 🤣
Considering the original email was also composed by GPT, it’s both 😆
@valentin_mll This is such a good implementation! thanks for sharing Sash
@valentin_mll Ay, thanks for the kind words!
@liquidx I want this for simplifying language for ESL speakers. I write so much technical documentation in my open-source projects that I know could really benefit from a one-touch "3rd grade reading level" filter/pass.
![Google presents AudioPaLM: A Large Language Model That Can Speak and Listen paper page: introduce AudioPaLM, a large language model for speech understanding and generation. AudioPaLM fuses text-based and speech-based language models, PaLM-2 [Anil et al., 2023] and AudioLM [Borsos et al., 2022], into a unified multimodal architecture that can process and generate text and speech with applications including speech recognition and speech-to-speech translation. AudioPaLM inherits the capability to preserve paralinguistic information such as speaker identity and intonation from AudioLM and the linguistic knowledge present only in text large language models such as PaLM-2. We demonstrate that initializing AudioPaLM with the weights of a text-only large language model improves speech processing, successfully leveraging the larger quantity of text training data used in pretraining to assist with the speech tasks. The resulting model significantly outperforms existing systems for speech translation tasks and has the ability to perform zero-shot speech-to-text translation for many languages for which input/target language combinations were not seen in training. AudioPaLM also demonstrates features of audio language models, such as transferring a voice across languages based on a short spoken prompt.](https://image.24vids.com/tw-1672048076469698561/ext_tw_video_thumb/1672047839378300928/pu/img/MuoOBsAyUd-HAI7D.jpg)
