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Along with text, images, video and code, Gemini is able to process raw audio signal end-to-end. 🔊 It can listen to and understand speech, making it not only useful for transcription but a model that has a much more nuanced perception of its environment. ↓

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Google DeepMind

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140,150 görüntüleme • 2 yıl önce •via X (Twitter)

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Kekius-Maximus.com profil fotoğrafı
Kekius-Maximus.com2 yıl önce

nice work

Adolfo Asorlin 👨🏼‍🚀 profil fotoğrafı
Adolfo Asorlin 👨🏼‍🚀2 yıl önce

This could lead to the development of more intelligent and helpful AI assistants, as well as more immersive and engaging experiences. I am eager to see what Gemini is capable of, and I am excited to see how it will shape the future of artificial intelligence. Thank you.

grate0x profil fotoğrafı
grate0x2 yıl önce

Very impressive work @GoogleDeepMind

Xi 🏴‍☠️ profil fotoğrafı
Xi 🏴‍☠️2 yıl önce

we're soo back

UNRAVEL FUTURE profil fotoğrafı
UNRAVEL FUTURE2 yıl önce

Impressive thou!

Esthefany Pinella profil fotoğrafı
Esthefany Pinella2 yıl önce

Y esto de los avances en la IA apenas comienza 🙌

BTB Finance profil fotoğrafı
BTB Finance2 yıl önce

Unbelievable

Dieter b/org profil fotoğrafı
Dieter b/org2 yıl önce

you are Gemini?

🥷SoundNinja🥷 profil fotoğrafı
🥷SoundNinja🥷2 yıl önce

Nice, thanks Google!

Joe Depp profil fotoğrafı
Joe Depp2 yıl önce

Cette innovation va engendrer une forte accélération dans le domaine de l'intelligence artificielle, comme on le constate par les usages exubérants dans cette vidéo. C'est une véritable prouesse d'être parvenu à un tel modèle eu égard au retard qu'avait google sur openai.

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🚨 ELON: GROK WILL BE ABLE TO UNDERSTAND IMAGES, VIDEOS AND BEHAVIORS “It does, it actually does understand images at this point. It certainly is intended to work in sync. It's intended to be what's called a multimodal model, which means understanding text, images, video, and audio.” Peterson: “Okay, if it understands video, will it start to understand behavior?” Elon: “Yeah.” Source: DW
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🚨 ELON: GROK WILL BE ABLE TO UNDERSTAND IMAGES, VIDEOS AND BEHAVIORS “It does, it actually does understand images at this point. It certainly is intended to work in sync. It's intended to be what's called a multimodal model, which means understanding text, images, video, and audio.” Peterson: “Okay, if it understands video, will it start to understand behavior?” Elon: “Yeah.” Source: DW

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Audio Transcription with Google Gemini 1.5 Flash In this video, Gemini-Flash was able to transcribe 13 minutes of audio in 50-60 seconds. I have tested this with multiple audio files, and the transcription accuracy is close to 99%. If the audio is clear, you get 100% correct transcription. Even if the audio is really bad with a lot of noise, you still get around 95-96% accuracy. The code for this is available on GitHub. If you're interested, you can download and run it. You just need a Google API key.
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Audio Transcription with Google Gemini 1.5 Flash In this video, Gemini-Flash was able to transcribe 13 minutes of audio in 50-60 seconds. I have tested this with multiple audio files, and the transcription accuracy is close to 99%. If the audio is clear, you get 100% correct transcription. Even if the audio is really bad with a lot of noise, you still get around 95-96% accuracy. The code for this is available on GitHub. If you're interested, you can download and run it. You just need a Google API key.

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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.
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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.

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I wanted to understand the proof and ended up making a video using opus 4.6. Still not completely happy with it, but maybe useful to others!
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I wanted to understand the proof and ended up making a video using opus 4.6. Still not completely happy with it, but maybe useful to others!

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