As of right now, one of the biggest problems with creating high quality audio is that it is difficult to create realistic sound effects with human voice actors. This can be done by utilizing generative adversarial networks (GANs), but this requires large amounts of data. One way to generate more data, in turn, could involve using virtual assistants such as Siri and Alexa. The problem is that these virtual assistants cannot read or understand language like humans do, so they can't produce realistic sounding voices. If we want them to do something more realistic, then we would need to train our own network with larger neural networks. This would require massive amounts of data, which is not necessarily scalable.
For those who don't know what GANs are, here's a brief explanation. At its core GANs consist of two main parts: an encoder and a decoder. An encoder consists of multiple layers where the output of one layer is fed into another layer. These layers are updated based on the inputted signal from the previous layer. There are multiple types of GANs out there, including Wasserstein GAN (WGAN), CycleGAN and others. We'll stick with the original Wasserstein GAN for now. In order to translate text into speech, you have to give the model a lot of examples and then ask it to produce new text that will sound similar to your speech.
Google has been showing interest in developing tools such as ChatGPT that can generate text, but I don't see any reason why they would make money off of generating voice data. However, if they ever wanted to monetize their services, they might go about it in a different way. They could start looking at other industries that demand data, such as entertainment, education and marketing. With the help of some sort of deep learning training techniques, they could train a network of AI models that could generate realistic sounding voices and content. This would allow Google to generate more revenue. It wouldn't exactly be able to replace traditional recording studios, but it could at least provide us with more creative content.
On top of being able to generate videos, images and other kinds of media, AI can also be used to generate music. Some researchers are investigating how to train GANs to generate sounds, and according to Dr. Sebastian Thrun, the creator of OpenAI's DALL·E project, this should be possible soon. A few years ago, Google started experimenting with OpenAI's "Generative Adversarial Network" to help generate songs, however, the results weren't particularly amazing.
So basically, GANs are very useful when it comes to image generation. But let's say you're making an animated video, which may look real good, but would not sound like anything else. You could use a generator to create fake text in order to get the same impression as the real thing. Or you could even add voiceovers to the end just for added effect. Another possibility would be to combine both animation and narration in a single video. Maybe people would love this idea, because they would feel that they're watching an actual movie. So, yeah, maybe we'll see soon that GANs do indeed work. What do YOU think? Let me know in comments!
In conclusion, while I'm not confident in the effectiveness of GANs when it comes to producing audio, AI technology definitely holds promise when it comes to creating artistic works, whether it's through art, music, writing or simply generating text. While many believe that GANs hold great potential, there are still concerns about the ethical implications of using the technology. Furthermore, as I mentioned before, big companies like Google have historically had difficulty finding ways to monetize their technologies, so perhaps they may take a slightly different approach. Regardless of whether they decide to develop a tool to generate voice data, we'll likely be seeing a lot more innovative applications of this technology for years to come. If you enjoyed this article, please subscribe to my blog, share it with your friends, leave a tip, or even consider pledging to support my writing.