Artificial IntelligenceGenerative AI

How To Develop an AI Text-to-Speech App

how-to-develop-text-to-speech-app

Have you ever used an AI Text-to-Speech (TTS) app? Yes, the same app that converts written texts into Generative AI-generated human-like voices. 

Isn’t it cool, right? Written text into human-like voices. But do you know how these apps are developed? What technologies do top mobile app developers leverage that turn written texts into speeches?  

If not, this blog is worth reading. We have explained the complete process of developing an AI text-to-speech app (Generative AI). Also, we have provided the strategies to monetize these apps as a bonus. 

So, let’s start the conversation! 

An Overview Of an AI Text-To-Speech Solution

An AI text-to-speech solution is an AI-powered text-to-speech converter mobile application or software that uses artificial intelligence and natural language processing algorithms to convert written text into speech. 

It is widely used as a personal reading assistant that reads out loud written documents, letters, books, web pages, etc. These apps also play a crucial role for people having issues with reading texts or suffering from Dyslexia.   

The market for AI text-to-speech apps is very lucrative as there is a high demand for these apps. Explore the market statistics in the next section. 

AI Text-to-Speech Applications: Latest Market Statistics

Look at the numbers given below to understand the market of AI-enabled text-to-speech converter apps. 

Source: Data Bridge

  1. Reports show the text-to-speech market will reach the value of $17.01 billion by 2029, growing at a CAGR of 30.20% during the period. 
  1. North America dominates the text-to-speech mobile application and software market. 
  1. Studies reveal that based on deployment, the cloud-based segment of text-to-speech apps dominated the market and is expected to grow lucratively in the future. 

Summing up the statistics, it is clear that the demand for AI text-to-speech will grow in the coming years. Thus, it will be profitable to develop a custom AI-powered text-to-speech app. 

Read the upcoming section to learn about developing an AI text-to-speech app in detail. 

How to Develop an AI Text-to-Speech App

The step-by-step guide to developing an AI-based text-to-speech app is as follows:

  1. Define the Requirements

To develop an AI text-to-speech app, the first and foremost step is to define the requirements for text-to-speech app development in detail. 

Understand the app’s purpose, its target audience, top-notch features and functionalities, and platforms it will support – Android, iOS, or cross-platform app development

  1. Set Up the Development Team

You will need to hire top AI app developers to build your AI-enabled text-to-speech mobile app. You can also outsource the app development to a leading mobile app development company that has expertise in developing AI text-to-speech apps. 

  1. Data Collection and Preprocessing

To train the AI text-to-speech model, you will need to gather a diverse dataset of text and matching audio recordings. Once you gather the text with audio recordings, clean and preprocess it thoroughly to ensure high-quality results. 

The data preprocessing includes: 

  • Text Normalization: the process of converting raw text into a standardized or canonical form. 
  • Tokenization: the process of breaking down a text or a sequence of characters into smaller units called tokens. 
  • Audio Feature Extraction: the process of extracting relevant features or characteristics from audio signals that capture important information about the sound’s properties, such as pitch, amplitude, frequency, and duration. 
  1. Model Training

After preprocessing the data, train the text-to-speech model leveraging deep learning techniques, such as recurrent neural networks (RNNs), convolutional neural networks (CNNs), or transformer architectures. 

You must fine-tune the model on the dataset you collected to optimize its performance and generate accurate results.  

  1. Test the Trained Model

Conduct rigorous testing of the trained model to ensure it is working precisely and delivering accurate results without any errors with different text inputs and languages.

  1. Design the UI 

With the assistance of UI designers, design an intuitive user interface for the text-to-speech app, having well-arranged icons and templates. 

The UI must be de-cluttered, allowing users to enter text, customize speech parameters, such as tone, speed, and voice level, and get desired speech results. 

  1. Develop the Text-to-Speech App 

Once the UI is designed, code the frontend and backend components of the AI text-to-speech app. Also, integrate the trained model into the app’s backend infrastructure. 

You need to ensure that the trained model communicates with other components, such as databases, Application Programming Interfaces (APIs), and user interfaces of the app seamlessly while developing the app.  

  1. Testing the App 

Post-development, test the AI text-to-speech app to identify bugs and fix them immediately. Moreover, evaluate the app’s compatibility with various devices and platforms, such as Android and iOS.  

You can also launch the Beta version of the app to test its functionality and performance and gather feedback from users simultaneously. 

  1. Launch the App 

After testing is done and your mobile app developers have made the necessary changes in the app, you can launch your AI text-to-speech app on Playstore and App Store. 

Moreover, you can also launch your AI text-to-speech app on cloud platforms like Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP), to align with the growing trend of cloud-based apps

  1. Regular Maintenance and Updates 

The job isn’t finished with the launch of the app. You need to monitor the performance of your AI text-to-speech app regularly. 

Also, you must keep integrating novel technologies and functionalities and fix bugs to keep the app relevant in the market for a long time.

So, this is how you develop an AI text-to-speech app. We have covered all the major stages of the development process. Still, if you need assistance regarding text-to-speech app development, reach out to our team!

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Must-Have Features of an AI Text-to-Speech App

The must-have features of an AI text-to-speech app are as follows: 

  1. Diverse Voices and Accents 

The foremost must-have feature of an AI text-to-speech mobile app is the set of diverse voice samples with suitable accents. The different kinds of voices and accents allow users to listen to text in different voices and accents. 

  1. Voice Tone Control 

The voice tone control feature allows users to set the tone of voice speech according to their preferences. For instance, if a user wants to listen to a scientific report in a formal tone, he can set the voice tone to formal and listen to the report. 

  1. Text Highlighting 

The text highlighting feature highlights the text that the voice is reading at the moment. This allows users to track the text and enhances the overall user experience. 

  1. Multi-Lingual Support 

The multi-lingual support helps users to listen to speech in their preferred language. For instance, if users want to read English text into Spanish, they can use this feature to translate it in real-time and listen to the text in Spanish. 

  1. Speed Control And Playback Options

With the speed control features, users can optimize the speed according to their choice. Moreover, they can also use the playback option to listen to the text-to-speech again. 

  1. Note-Taking Feature 

As the name suggests, the note-taking feature allows the user to take crucial notes while listening to the speech. 

  1. Personalization

The personalization allows users to customize the user interface as per their wish. This feature plays a crucial role in enhancing the user experience of the AI text-to-speech app. 

  1. Offline Functionality 

The offline functionality allows the users to use the AI text-to-speech app without an internet connection. 

So, these are some must-have features of an AI text-to-speech mobile application. Now, let’s proceed to the technology stack you require to develop an AI text-to-speech app. 

Technology Stack to Develop an AI Text-to-Speech App 

The following technology stack is used to build a text-to-speech mobile app. 

  1. Text Processing: Natural Language Processing (NLP) libraries like NLTK, SpaCy, or TensorFlow.
  1. Speech Synthesis Models: Deep learning frameworks like TensorFlow or PyTorch. 
  1. Data Handling: Data storage solutions, such as SQL or NoSQL databases. 
  1. API Integration: RESTful APIs for external services or cloud platforms. For example, Google Cloud Text-to-Speech API, and IBM Watson Text-to-Speech. 
  1. Frontend Development: HTML, CSS, JavaScript, and front-end frameworks like React or Angular for user interface development. 
  1. Backend Development: Server-side languages, such as Python and Node.js for handling requests, business logic, and integrating with APIs. 
  1. Deployment: Cloud platforms, such as AWS, Google Cloud Platform, and Microsoft Azure for hosting, scaling, and managing the application on Cloud. 
  1. Version Control: Git for managing source code and collaboration. 
  1. Testing: Jest and PyTest for testing individual components, integration testing, and end-to-end testing. 
  1. Monitoring: Monitoring tools, such as Prometheus and Grafana for tracking application performance, logs, and errors. 


Thus, this is the recommended technology stack to develop an AI text-to-speech app. Please note that these technologies are just suggestions, you can choose other technologies and tools according to your specific needs. 

Benefits of Developing an AI-based Text-to-Speech App 

There are numerous benefits to developing an AI text-speech app. A few of them are: 

  1. Convenience for Users 

The major benefit of developing an AI text-to-speech app is providing convenience to users to listen to long forms of written text in their favorite voice speeches.

  1. Saves Time

Using AI text-to-speech apps, users can listen to books, news, letters, website content, etc. while doing other chores. This helps them multitasking and saves them a lot of time. 

  1. Help People With Disabilities

Text-to-speech apps help people with disabilities significantly who aren’t able to read properly. These apps can translate the text into speeches, hence allowing them to listen to the audio form of the text. 

  1. Generate Additional Revenue 

By monetizing text-to-speech mobile apps, you can generate additional revenue through subscriptions, or in-app purchases. 

  1. Enhance Brand Image 

The demand for AI text-to-speech apps is growing exponentially. Hence developing an app will help you gain a competitive edge in the market and enhance your brand image.   

Therefore, these are the top benefits of developing an AI text-to-speech app. Read further to explore the best strategies to monetize your text-to-speech converter mobile app. 

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Monetizing Strategies for AI Text-to-Speech Mobile Apps

The following are the proven strategies to monetize AI text-to-speech mobile apps. 

  1. Freemium

The best strategy to monetize an AI text-to-speech app is the Freemium model. In freemium, users can use the app for free with basic features. Likewise, to access advanced features and premium speech voices, they need to buy the premium version of the app. 

  1. Subscription

Another proven way to monetize the text-to-speech app is to make it subscription-based. To use the app, users need to buy the subscription package, mainly available in monthly, quarterly, half-yearly, and yearly packages. 

  1. In-app Advertising

In-app advertising is one of the top monetizing strategies that most text-to-speech apps use. In this strategy, you run ads for other brands and earn revenue. 

  1. In-app Purchases

In-app purchases let users buy additional items, such as voices, languages, specialized features, etc. You can offer users to buy specific items to enhance their experience within the app and generate revenue. 

So, these are the top ways to monetize an AI text-to-speech mobile application. 

Use Cases of AI Text-to-Speech Apps   

The AI text-to-speech apps are used for various purposes. The top use cases of AI text-to-speech apps are as follows: 

  1. Accessibility to People With Disability 

As discussed before, AI text-to-speech apps help people with disability, including people suffering from visual impairments, dyslexia, or other reading difficulties. They can leverage AI text-to-speech apps to access written text in audio form. 

  1. Voice-Based Assistants 

AI text-to-speech apps are also used as voice-based smart personal assistants and help users read long-written texts in the tone and accent users prefer. These apps are used to access documents, web pages, formal letters, news, etc. 

  1. Customer Support

AI-powered text-to-speech apps are used by startups, and mid-size and large-scale businesses for customer support. The text-to-speech technology is integrated into an AI-based chatbot to provide automated responses to customer queries around the clock. This enhances the overall customer satisfaction. 

  1. Content Creation 

The text-to-speech apps are commonly used in the content creation industry. Content creators use these apps to generate voiceovers for videos, podcasts, audiobooks, and other multimedia content. These apps save time and other resources compared to hiring voice-over artists.

  1. Language Learning and Translation 

Last but not least, users leverage AI text-to-speech apps to learn new languages, pronounce words and phrases accurately, and translate written texts into other languages in real-time. 

Therefore, these are the top use cases of AI text-to-speech apps. These apps are used in various industry verticals, such as healthcare, e-commerce, manufacturing, finance, and more. 

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Concluding Thoughts 

So, this is your ultimate guide to developing an AI text-to-speech app. We have covered all the crucial points and development stages in this blog. 

Text-to-speech apps are crucial tools that act as personal assistants who read long-written texts for users. Plus, users can customize the dialect, language, speed, and tone of the speech as per their choice. 

These apps’ popularity is gaining momentum, thus it is the right time to develop a custom text-to-speech mobile app.

Need professional assistance for the development? Feel free to reach out to our experts and get your text-to-speech app development started! Visit our website: www.quytech.com

Frequently Asked Questions

Here are some frequently asked questions regarding AI text-to-speech app development. 

Q- What are AI text-to-speech mobile apps? 

AI text-to-speech apps are mobile applications and software that convert written text into speeches in real-time using the potential of artificial intelligence and natural language processing. 

Q- Is it a good idea to build an AI text-to-speech app when there are similar apps already available? 

Yes, there are numerous text-to-speech apps available, but with the right development approach and advanced features and functionalities, you can develop a text-to-speech app that can surpass all the other apps. 

Q- Can I build an AI text-to-speech app all by myself? 

AI text-to-speech app development requires in-depth knowledge of mobile app development and AI. Hence, it is quite difficult for a person to develop an AI text-to-speech app all by himself. 

Q- How can I make my text-to-speech app stand out? 

You can make your text-to-speech app stand out by providing your users with the value that the competition does not provide. You need to research the competitors and market thoroughly to identify the weak points and solve them by adding advanced features to your text-to-speech app. 

Q- How much does it cost to develop a custom AI text-to-speech mobile app? 

The cost of developing a custom AI text-to-speech mobile app depends on various factors, such as the type of app, tools and technologies used, the size and location of the development team, and more. Hence, we recommend you contact our team and share your ideas and requirements to learn about the cost of AI text-to-speech app development.