Easily Create Voiceovers Using OpenAI's New Text to Speech and Vision Models

Ian Wootten
10 Nov 202315:09

TLDRIn an exciting Open AI Dev Day, developers were introduced to new API updates including GPT-3.5 Turbo, expanded context windows, and lower prices. Within 24 hours, innovative applications were created, such as a sarcastic website roasting tool and a sports commentary generator. The video demonstrates how to utilize Open AI's text-to-speech and vision APIs to create audio feedback and video voiceovers, showcasing the potential for AI in content creation and web design.

Takeaways

  • 🚀 OpenAI's first Dev Day introduced several new products and API updates, including GPT-3.5 Turbo, 128 context windows, and lower prices for the API.
  • 🔊 Developers have already started building applications using the new APIs, such as a sarcastic website roasting tool and sports commentary for videos.
  • 🗣️ The introduction of the D3 API allows for more advanced and interactive applications.
  • 📝 To utilize OpenAI's services, developers need to set up a virtual environment with the latest OpenAI client.
  • 🔧 The process involves installing the OpenAI client using pip and loading an API key from a configuration file.
  • 🎤 The text-to-speech model can be used to generate audio files, which can be further enhanced with command-line interfaces.
  • 🖼️ The GPT-4 Vision API can provide feedback on website design and UX, with the ability to process images and generate descriptions.
  • 🎥 For video processing, OpenCV can be used to extract frames, which can then be sent to OpenAI for text description generation.
  • 🗣️ The text descriptions from images can be used to create voiceover scripts for videos, adding a narrative to visual content.
  • 📚 The script provides a detailed example of how to use OpenAI's APIs for creating a voiceover for a video, showcasing the potential of the technology.
  • 🌟 The potential applications of these APIs are vast, and the community is excited to explore and build new innovative solutions.

Q & A

  • What new products and updates were announced by OpenAI during their first Dev day?

    -OpenAI announced several new products and updates, including GPT-3.5 (GPT Turbo), 128-context windows, lower prices for the API, the Assistance API, Vision and Text-to-Speech, and the introduction of the DALL·E 3 API.

  • How did developers respond to the new OpenAI announcements within 24 hours?

    -Developers started building exciting projects using the new APIs, such as a website roasting tool with a sarcastic voice and a sports commentary tool for videos.

  • What is the purpose of the website roasting tool mentioned in the script?

    -The website roasting tool takes a URL for a website and creates feedback on the website's design and content in a sarcastic voice.

  • How does the sports commentary tool work?

    -The sports commentary tool generates a one-man show commentary for a video, providing a dynamic and engaging description of the action.

  • What are the steps to get OpenAI's Text-to-Speech model to work?

    -To use the Text-to-Speech model, one needs to create a virtual environment with the latest OpenAI client installed, activate the environment, and then install the client using pip. An API key from OpenAI is required for authentication.

  • What is the role of the 'typer' package in the script?

    -The 'typer' package is used to create a command-line interface for the script, allowing users to pass arguments and interact with the AI through the command line.

  • How does the script use the screenshot package to capture website images?

    -The screenshot package is used to take a screenshot of any website by providing a URL and a file name, and it writes the screenshot to the specified file.

  • What is the purpose of the feedback command in the script?

    -The feedback command uses the GPT-4 Vision API to provide expert feedback on web design, UX, and copywriting based on an image or screenshot of a website.

  • How does the script handle the creation of a voiceover for a video?

    -The script uses OpenCV to extract frames from a video, encodes them in base64, and sends them to OpenAI to generate text descriptions. These descriptions are then used to create a voiceover script, which is converted into an MP3 file.

  • What is the significance of the 'context window' in the script?

    -The context window refers to the amount of text that the AI can process at once. In the script, it is mentioned that a large context window (128k) is used for processing the video frames, which helps in generating more detailed and accurate responses.

  • What are the limitations of the voices available in the Text-to-Speech API?

    -The voices available in the Text-to-Speech API have a limited range of emotions and cannot be adjusted for enthusiasm or tone. The emotional range is determined by the specific voice chosen by the user.

Outlines

00:00

🚀 OpenAI's Dev Day Announcements

The first paragraph discusses the recent OpenAI Developer Day, which introduced several new products and API updates. These include GPT-3.5 Turbo, 128 context windows, lower prices, and the introduction of the DALL·E 3 API. Developers have already started building applications using these new features, such as a sarcastic website roasting tool and a sports commentary generator. The speaker also explains how to use the new text-to-speech API, including setting up a virtual environment and installing the OpenAI client.

05:01

🖼️ Web Design Feedback with GPT-4 Vision

In the second paragraph, the focus shifts to using the GPT-4 Vision API for web design feedback. The speaker demonstrates how to take a screenshot of a website, encode it, and use the API to generate feedback on web design, UX, and copywriting. The process is wrapped into a command-line interface using the typer tool. The speaker also discusses how to combine this with text-to-speech to create audio feedback, using their own website as an example.

10:03

🎥 Creating Voiceovers for Videos

The third paragraph describes the process of creating voiceovers for videos using OpenAI's APIs. The speaker uses the GPT-4 Vision API to generate text descriptions from video frames, which are then converted into a voiceover script. They demonstrate this by creating a voiceover for the 'Big Buck Bunny' video, using the David Attenborough style. The speaker also mentions the importance of not exceeding context limits when sending multiple images to the API.

Mindmap

Keywords

💡OpenAI

OpenAI is an artificial intelligence research lab that develops and shares AI technologies. In the video, OpenAI is mentioned as the creator of various APIs that the speaker is excited about, such as GPT-3.5 and GPT-4, which are used for text generation and other AI tasks.

💡Dev Day

Dev Day refers to a day or event where developers gather to learn about new tools, updates, and technologies. In this context, OpenAI's first Dev Day is highlighted for announcing new products and API updates, which are of significant interest to the speaker and the developer community.

💡API

API stands for Application Programming Interface, which is a set of rules and protocols that allow different software applications to communicate with each other. The video discusses various OpenAI APIs like GPT-3.5, GPT-4, and others that enable developers to integrate AI capabilities into their own applications.

💡GPT-3.5 and GPT-4

GPT-3.5 and GPT-4 are versions of Generative Pre-trained Transformer models developed by OpenAI. These models are capable of generating human-like text and understanding context, which is a significant advancement in natural language processing. The video showcases the potential of these models by demonstrating their use in creating voiceovers and website feedback.

💡Text-to-Speech (TTS)

Text-to-Speech is a technology that converts written text into spoken words. In the video, the speaker uses OpenAI's TTS model to generate audio from text, creating a sarcastic voiceover for a website and a sports commentary, showcasing the versatility and quality of the AI's voice synthesis capabilities.

💡Vision API

The Vision API is a service that allows developers to integrate image recognition and processing capabilities into their applications. In the video, the speaker uses the Vision API to analyze screenshots of a website and provide feedback, demonstrating the API's ability to understand and describe visual content.

💡Virtual Environment

A virtual environment is a isolated space for running a Python application, allowing for the creation of an environment with its own dependencies. The video mentions setting up a virtual environment to install and use the OpenAI client, which is essential for developers to manage the libraries and dependencies required for AI development.

💡Typer

Typer is a Python library for creating command-line interfaces. The speaker uses Typer to wrap the AI functions into a CLI, making it easier to interact with the AI models from the command line. This tool enhances the user experience by allowing arguments to be passed directly to the AI functions.

💡Screenshot

A screenshot is a digital image taken by the computer screen capturing specific content. The video discusses using a package called 'screenshot' to capture images of a website, which are then processed by the Vision API to provide feedback on web design and UX.

💡Voiceover

Voiceover refers to a production technique in which a voice recording is created for use in a video, film, or other visual media. In the video, the speaker demonstrates how to create a voiceover script for a video using the AI's text generation capabilities, showcasing the AI's ability to understand and describe visual content for storytelling purposes.

💡OpenCV

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. The video mentions using OpenCV to process video frames and extract images for analysis by the Vision API, highlighting the integration of different AI technologies for complex tasks.

Highlights

OpenAI's first Dev Day introduced new products and API updates.

GPT-3.5 Turbo, 128 context windows, and lower prices for the API were announced.

New APIs include Assistance API, Vision API, and Text-to-Speech.

Developers are already building exciting applications with the new APIs.

An example is a website roasting tool that provides sarcastic feedback.

Another example is sports commentary for a video using the Texas speech and vision APIs.

The process of getting OpenAI to talk involves using the new audio speech create endpoint.

A virtual environment with the latest OpenAI client is required to use the API.

The OpenAI key can be generated on the OpenAI platform.

The text-to-speech model can be used to create audio files from text.

Typer is used to create a command-line interface for the text-to-speech function.

The vision API can provide feedback on web design, UX, and copywriting.

Screenshots of websites can be created using the screenshot package.

The GPT-4 Vision preview model can generate text descriptions from images.

Video voiceovers can be created by encoding frames and using text-to-speech.

OpenCV is used to process video frames for voiceover creation.

The voiceover script is generated in the style of a BBC narrator.

The API calls allow for the creation of complex applications with minimal effort.

The potential for building innovative applications with these APIs is vast.