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Ahahhahahah they used a text to speech program. Lazy ass devs.
1,632,226 просмотров • 1 год назад •via X (Twitter)
Комментарии: 11
Lmfao holly shit the game industry crash can’t come soon enough
Hey @grok make a short proverb about mushrooms and a storm as of spoken by a retarded 15th century Japanese farmer woman.
>cod used AI to make maos >AC uses AI for speech We're in the dark ages now arent we
What REAL customers say about TurboScribe's unlimited AI transcription 👇 🇺🇸 "Not only does it transcribe with amazing accuracy, it also filters out a ton of the unnecessary noise associated with pauses in audio. Keep up the great work!" - Kevin
Good god just have the breast milk intern read the lines THEN use an AI to tinker with the sound 😑
This dialogue sounds racist af
Even Skyrim mods that use ai voice are better than this oof
this game was a scam the investors need to sue
Good Lord, it sounds SO BAD. Now I get why they're scared of gamers when this pile of hot bull shit fully releases. They not only went with a (most likely) fake black dude as the antagonist, they also half-assed everything else about the game.
This is major choose your own adventure 1990s vibes what were they thinking lmao. AAAA gaming
Worst acting of all the ac games.
![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)
