3 Practical Tips to Boost Your Business with AI Voice Cloning Technology

Paulina Lewandowska

15 Mar 2023
3 Practical Tips to Boost Your Business with AI Voice Cloning Technology

Introduction

AI Voice cloning technology has been gaining popularity in recent years, and for good reason. With the ability to create realistic and natural-sounding voices, businesses can now leverage this technology to enhance their customer experience and improve their bottom line. In this blog post, we'll explore three practical tips for using AI voice cloning technology to boost your business. So whether you're a small business owner or a large corporation, read on to learn how you can take advantage of this game-changing technology.

Types of AI voice cloning technology

Text-to-speech synthesis is a sort of AI voice cloning technology. In order to do this, a computer program that can read text aloud in a certain voice must be developed. To produce speech that resembles a particular person's voice, the program examines the text and applies algorithms. This can be helpful for developing personal voice interfaces or more realistic virtual assistants. 

Voice conversion is a different subset of AI voice cloning. This is taking a vocal recording of a person and altering it with algorithms to create a different voice. This can help create text-to-speech software that sounds more realistic by, for instance, changing a robotic voice into a more human-sounding one.

Prime Voice AI

Prime Voice AI is an example of a product which is a game-changer in AI voice cloning technology. This sophisticated and adaptable software created by Eleven uses deep learning models to produce human-like intonation and inflection with unmatched fidelity. The generation of high-quality spoken audio in any voice and style for a variety of applications, including narrative, news stories, newsletters and blogs, audiobooks, and more, is now possible for content producers, publishers, and developers. 

One of Prime Voice AI's key benefits is its capacity to produce emotions and laughter in AI-generated voices, which makes the audio content more interesting and lifelike. Using the tool's generative model, users can also copy already-existing voices from samples or build brand-new synthetic voices from start.

Also, the program provides a cutting-edge text-to-speech (TTS) model that enables users to turn any written work into flawless professional audio at a fraction of the time and cost often associated with recording. Moreover, Prime Voice AI includes a voice lab where users may clone and build artificial voices as well as a Projects workstation where users have complete control over the creative process and can guide and edit narration.

How AI cloning technology can improve your business?

Here are 3 practical tips on how your business can benefit from this cutting-edge technology:

Personalized Customer Support

AI voice cloning technology can be utilized to build virtual assistants that can offer customers customer care that is tailored to their needs. The virtual assistant can serve clients in a more personalized and effective way by mimicking a company representative's voice. It is possible to program the virtual assistant to respond to frequently asked inquiries, offer information about the products, and even address consumer concerns. This may boost customer retention and improve customer satisfaction.

Audio Marketing

Audio commercials can be produced using AI voice cloning technology that seem more realistic and interesting. The ability of the technology to duplicate a firm spokesperson's or brand ambassador's voice helps strengthen connections with the target market. This may help to raise brand recognition, foster trust, and eventually enhance sales.

Language Localization

Audio content can be globalized for many locales and languages using AI voice cloning technology. To produce audio material that resonates better with the local audience, a business can, for instance, clone the voice of a local spokesperson or star. This can help to build brand awareness across several geographies and boost the efficacy of marketing campaigns.

How far are we?

Users can currently clone their own voices or already-existing voices from samples using the voice cloning tool. We may state that we are quite advanced in this field based on the fact that the tool uses a cloning model that can learn any speech profile based on just a minute of audio, without the requirement for training. 

To examine and understand the voice rhythms, intonation, and other speech traits of the target voice, deep learning models are used. The cloned voice that emerges is incredibly realistic and suitable for a range of uses, including voice acting in video games and other media as well as audiobooks and podcasts.

Additionally, the product offers a voice lab with more sophisticated features for voice cloning and artificial voice generation. With the help of this function, users can generate brand-new synthetic voices from scratch or alter pre-existing voices to produce distinctive and individualized sounds. The voice lab feature is very sophisticated and needs some technical know-how, but it gives users a lot of flexibility and creative freedom to produce original and compelling audio content.

Conclusion

In conclusion, AI voice cloning technology imitates and mimics a person's speech using artificial intelligence algorithms. With the aid of this technology, a computer program may listen to audio recordings of individuals and then produce fresh speech that sounds just like them. With the help of deep learning models, which study and learn speech patterns and voice patterns, it is now possible to copy existing voices from samples or even an individual's own voice. The cloned voices that are produced are incredibly realistic and can be used in a variety of contexts, including podcasts and audiobooks. Those who wish to produce original and captivating audio material have more flexibility and creativity thanks to sophisticated features like voice labs.

Lately, we also published a list of AI tools which streamline and accelerate everyday work, check on here.

Tagi

Most viewed


Never miss a story

Stay updated about Nextrope news as it happens.

You are subscribed

AI in Real Estate: How Does It Support the Housing Market?

Miłosz Mach

18 Mar 2025
AI in Real Estate: How Does It Support the Housing Market?

The digital transformation is reshaping numerous sectors of the economy, and real estate is no exception. By 2025, AI will no longer be a mere gadget but a powerful tool that facilitates customer interactions, streamlines decision-making processes, and optimizes sales operations. Simultaneously, blockchain technology ensures security, transparency, and scalability in transactions. With this article, we launch a series of publications exploring AI in business, focusing today on the application of artificial intelligence within the real estate industry.

AI vs. Tradition: Key Implementations of AI in Real Estate

Designing, selling, and managing properties—traditional methods are increasingly giving way to data-driven decision-making.

Breakthroughs in Customer Service

AI-powered chatbots and virtual assistants are revolutionizing how companies interact with their customers. These tools handle hundreds of inquiries simultaneously, personalize offers, and guide clients through the purchasing process. Implementing AI agents can lead to higher-quality leads for developers and automate responses to most standard customer queries. However, technical challenges in deploying such systems include:

  • Integration with existing real estate databases: Chatbots must have access to up-to-date listings, prices, and availability.
  • Personalization of communication: Systems must adapt their interactions to individual customer needs.
  • Management of industry-specific knowledge: Chatbots require specialized expertise about local real estate markets.

Advanced Data Analysis

Cognitive AI systems utilize deep learning to analyze complex relationships within the real estate market, such as macroeconomic trends, local zoning plans, and user behavior on social media platforms. Deploying such solutions necessitates:

  • Collecting high-quality historical data.
  • Building infrastructure for real-time data processing.
  • Developing appropriate machine learning models.
  • Continuously monitoring and updating models based on new data.

Intelligent Design

Generative artificial intelligence is revolutionizing architectural design. These advanced algorithms can produce dozens of building design variants that account for site constraints, legal requirements, energy efficiency considerations, and aesthetic preferences.

Optimizing Building Energy Efficiency

Smart building management systems (BMS) leverage AI to optimize energy consumption while maintaining resident comfort. Reinforcement learning algorithms analyze data from temperature, humidity, and air quality sensors to adjust heating, cooling, and ventilation parameters effectively.

Integration of AI with Blockchain in Real Estate

The convergence of AI with blockchain technology opens up new possibilities for the real estate sector. Blockchain is a distributed database where information is stored in immutable "blocks." It ensures transaction security and data transparency while AI analyzes these data points to derive actionable insights. In practice, this means that ownership histories, all transactions, and property modifications are recorded in an unalterable format, with AI aiding in interpreting these records and informing decision-making processes.

AI has the potential to bring significant value to the real estate sector—estimated between $110 billion and $180 billion by experts at McKinsey & Company.

Key development directions over the coming years include:

  • Autonomous negotiation systems: AI agents equipped with game theory strategies capable of conducting complex negotiations.
  • AI in urban planning: Algorithms designed to plan city development and optimize spatial allocation.
  • Property tokenization: Leveraging blockchain technology to divide properties into digital tokens that enable fractional investment opportunities.

Conclusion

For companies today, the question is no longer "if" but "how" to implement AI to maximize benefits and enhance competitiveness. A strategic approach begins with identifying specific business challenges followed by selecting appropriate technologies.

What values could AI potentially bring to your organization?
  • Reduction of operational costs through automation
  • Enhanced customer experience and shorter transaction times
  • Increased accuracy in forecasts and valuations, minimizing business risks
Nextrope Logo

Want to implement AI in your real estate business?

Nextrope specializes in implementing AI and blockchain solutions tailored to specific business needs. Our expertise allows us to:

  • Create intelligent chatbots that serve customers 24/7
  • Implement analytical systems for property valuation
  • Build secure blockchain solutions for real estate transactions
Schedule a free consultation

Or check out other articles from the "AI in Business" series

AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

Gracjan Prusik

11 Mar 2025
AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

AI Revolution in the Frontend Developer's Workshop

In today's world, programming without AI support means giving up a powerful tool that radically increases a developer's productivity and efficiency. For the modern developer, AI in frontend automation is not just a curiosity, but a key tool that enhances productivity. From automatically generating components, to refactoring, and testing – AI tools are fundamentally changing our daily work, allowing us to focus on the creative aspects of programming instead of the tedious task of writing repetitive code. In this article, I will show how these tools are most commonly used to work faster, smarter, and with greater satisfaction.

This post kicks off a series dedicated to the use of AI in frontend automation, where we will analyze and discuss specific tools, techniques, and practical use cases of AI that help developers in their everyday tasks.

AI in Frontend Automation – How It Helps with Code Refactoring

One of the most common uses of AI is improving code quality and finding errors. These tools can analyze code and suggest optimizations. As a result, we will be able to write code much faster and significantly reduce the risk of human error.

How AI Saves Us from Frustrating Bugs

Imagine this situation: you spend hours debugging an application, not understanding why data isn't being fetched. Everything seems correct, the syntax is fine, yet something isn't working. Often, the problem lies in small details that are hard to catch when reviewing the code.

Let’s take a look at an example:

function fetchData() {
    fetch("htts://jsonplaceholder.typicode.com/posts")
      .then((response) => response.json())
      .then((data) => console.log(data))
      .catch((error) => console.error(error));
}

At first glance, the code looks correct. However, upon running it, no data is retrieved. Why? There’s a typo in the URL – "htts" instead of "https." This is a classic example of an error that could cost a developer hours of frustrating debugging.

When we ask AI to refactor this code, not only will we receive a more readable version using newer patterns (async/await), but also – and most importantly – AI will automatically detect and fix the typo in the URL:

async function fetchPosts() {
    try {
      const response = await fetch(
        "https://jsonplaceholder.typicode.com/posts"
      );
      const data = await response.json();
      console.log(data);
    } catch (error) {
      console.error(error);
    }
}

How AI in Frontend Automation Speeds Up UI Creation

One of the most obvious applications of AI in frontend development is generating UI components. Tools like GitHub Copilot, ChatGPT, or Claude can generate component code based on a short description or an image provided to them.

With these tools, we can create complex user interfaces in just a few seconds. Generating a complete, functional UI component often takes less than a minute. Furthermore, the generated code is typically error-free, includes appropriate animations, and is fully responsive, adapting to different screen sizes. It is important to describe exactly what we expect.

Here’s a view generated by Claude after entering the request: “Based on the loaded data, display posts. The page should be responsive. The main colors are: #CCFF89, #151515, and #E4E4E4.”

Generated posts view

AI in Code Analysis and Understanding

AI can analyze existing code and help understand it, which is particularly useful in large, complex projects or code written by someone else.

Example: Generating a summary of a function's behavior

Let’s assume we have a function for processing user data, the workings of which we don’t understand at first glance. AI can analyze the code and generate a readable explanation:

function processUserData(users) {
  return users
    .filter(user => user.isActive) // Checks the `isActive` value for each user and keeps only the objects where `isActive` is true
    .map(user => ({ 
      id: user.id, // Retrieves the `id` value from each user object
      name: `${user.firstName} ${user.lastName}`, // Creates a new string by combining `firstName` and `lastName`
      email: user.email.toLowerCase(), // Converts the email address to lowercase
    }));
}

In this case, AI not only summarizes the code's functionality but also breaks down individual operations into easier-to-understand segments.

AI in Frontend Automation – Translations and Error Detection

Every frontend developer knows that programming isn’t just about creatively building interfaces—it also involves many repetitive, tedious tasks. One of these is implementing translations for multilingual applications (i18n). Adding translations for each key in JSON files and then verifying them can be time-consuming and error-prone.

However, AI can significantly speed up this process. Using ChatGPT, DeepSeek, or Claude allows for automatic generation of translations for the user interface, as well as detecting linguistic and stylistic errors.

Example:

We have a translation file in JSON format:

{
  "welcome_message": "Welcome to our application!",
  "logout_button": "Log out",
  "error_message": "Something went wrong. Please try again later."
}

AI can automatically generate its Polish version:

{
  "welcome_message": "Witaj w naszej aplikacji!",
  "logout_button": "Wyloguj się",
  "error_message": "Coś poszło nie tak. Spróbuj ponownie później."
}

Moreover, AI can detect spelling errors or inconsistencies in translations. For example, if one part of the application uses "Log out" and another says "Exit," AI can suggest unifying the terminology.

This type of automation not only saves time but also minimizes the risk of human errors. And this is just one example – AI also assists in generating documentation, writing tests, and optimizing performance, which we will discuss in upcoming articles.

Summary

Artificial intelligence is transforming the way frontend developers work daily. From generating components and refactoring code to detecting errors, automating testing, and documentation—AI significantly accelerates and streamlines the development process. Without these tools, we would lose a lot of valuable time, which we certainly want to avoid.

In the next parts of this series, we will cover topics such as:

Stay tuned to keep up with the latest insights!