Text-to-Speech (TTS) is the task of generating natural sounding speech given text input. TTS models can be extended to have a single model that generates speech for multiple speakers and multiple languages.
Build a Text-to-Speech App | AI Engineer
Here are terms definitions related to text-to-speech (TTS) models:
Text-to-speech (TTS): The task of converting text into speech. TTS models are trained on large datasets of text and speech, and they can generate speech in a variety of languages and voices.
Natural sounding speech:Speech that sounds like it was produced by a human. TTS models have made significant progress in recent years in generating natural-sounding speech.
Speaker:The person or character who is speaking. TTS models can be trained to generate speech for multiple speakers, with different voices and accents.
Language:The system of communication used by a particular community or nation. TTS models can be trained to generate speech in multiple languages.
Multi-speaker TTS model:A TTS model that can generate speech for multiple speakers, with different voices and accents.
Multi-lingual TTS model:A TTS model that can generate speech in multiple languages.
Text-to-speech (TTS) models are a type of artificial intelligence (AI) that can convert text into natural-sounding speech. TTS models are trained on large datasets of text and speech, and they can generate speech in a variety of languages and voices.
TTS models are used in a variety of applications, including:
Accessibility:TTS models can be used to help people who are blind or have low vision access information and services. For example, a TTS model can be used to read text aloud from a website or to provide audio descriptions of videos.
Education:TTS models can be used to create educational materials that are more engaging and accessible to students. For example, a TTS model can be used to create audio versions of textbooks or to generate interactive learning experiences.
Customer service:TTS models can be used to create customer service chatbots that can provide assistance to customers in a more natural and efficient way.
Entertainment:TTS models can be used to create audiobooks, podcasts, and other forms of entertainment.
Productivity:TTS models can be used to create tools that can help people to be more productive, such as tools that can read emails aloud or generate transcripts of meetings.
Here are some specific examples of how TTS is used in the use cases you mentioned:
Voice assistants:TTS models are used to create voice assistants on smart devices, such as Amazon Alexa and Google Assistant. These voice assistants can be used to control smart home devices, get information, and perform a variety of other tasks.
Announcement systems:TTS models are widely used in airport and public transportation announcement systems. These systems use TTS to convert text announcements into speech, which can be heard by passengers.
Navigation systems:TTS models are used in navigation systems to provide spoken directions to drivers and pedestrians.
E-learning:TTS models are used in e-learning platforms to create audio versions of course materials. This can make learning more accessible to students who have visual impairments or who learn better by listening.
Gaming:TTS models are used in video games to create voice acting for characters and to provide spoken feedback to players.
TTS models are still under development, but they have already made significant progress in recent years. TTS models can now generate speech that is very close to human quality, and they are becoming increasingly affordable and accessible.
Here are some examples of popular TTS models:
Google Cloud Text-to-Speech
IBM Watson Text-to-Speech
Microsoft Azure Text-to-Speech
TTS models are a powerful tool that can be used to improve the accessibility, engagement, and efficiency of a wide range of applications.
How to Build a Text-to-Speech App with a Custom Voice
To build custom modules for a custom text-to-speech (TTS) voice, you will need to:
Collect a dataset of the individual's voice.This dataset should include a variety of sentences and phrases, spoken in different tones and contexts.
Choose a TTS model.There are many different TTS models available, both open source and commercial. Choose a model that is well-suited for your specific needs, such as the type of voice you want to create and the languages you need to support.
Train the TTS model on the dataset of the individual's voice.This process can be time-consuming and computationally expensive, depending on the size and complexity of the dataset and the TTS model you are using.
Evaluate the trained TTS model.Once the model is trained, you need to evaluate its performance on a held-out test dataset. This will help you to identify any areas where the model needs improvement.
Create modules for the trained TTS model.Once you are satisfied with the model's performance, you need to create modules that can be used to generate speech from text. These modules can be implemented in a variety of ways, depending on the programming language and platform you are using.
Here are some additional tips for building custom modules for a custom TTS voice:
Use a high-quality dataset of the individual's voice. The larger and more diverse the dataset, the better the TTS model will be able to learn the individual's voice patterns.
Choose a TTS model that is well-suited for your specific needs. For example, if you need to create a voice that can speak multiple languages, you will need to choose a TTS model that supports those languages.
Train the TTS model on a powerful computer. Training a TTS model can be computationally expensive, so it is important to use a computer that has enough processing power and memory.
Evaluate the trained TTS model carefully. Listen to the generated speech and compare it to the individual's voice. Make sure that the generated speech sounds natural and that it accurately reflects the individual's voice patterns.
Create modules for the trained TTS model that are easy to use. For example, you could create a library that can be used to generate speech from text in different programming languages.
Once you have created modules for the trained TTS model, you can use them to generate custom text-to-speech voices for a variety of applications.
Here are some examples of how you can use custom modules for a custom TTS voice:
Create a custom voice for your voice assistant.You could use a custom TTS voice to create a voice assistant that sounds like you. This could be useful for a variety of tasks, such as controlling your smart home devices or getting directions to your destination.
Create a custom voice for your audiobook or podcast.You could use a custom TTS voice to create an audiobook or podcast that sounds like you. This could be a great way to share your stories with the world.
Create a custom voice for your video game character.You could use a custom TTS voice to create a video game character that sounds like you. This could help to create a more immersive and engaging gaming experience.
These are just a few examples of how you can use custom modules for a custom TTS voice. As TTS technology continues to improve, we can expect to see even more innovative and creative uses of custom TTS voices in the future.
Open Source text-to-speech (TTS) models
There are many open source text-to-speech (TTS) models available. Here are a few of the most popular:
Coqui AI TTS:This TTS model is trained on a large dataset of text and audio, and it can generate speech in a variety of languages.
Tacotron2:This TTS model is known for its high-quality speech output. It is trained on a large dataset of text and audio, and it can generate speech in a variety of languages.
WaveNet:This TTS model is known for its ability to generate speech that sounds very natural. It is trained on a large dataset of text and audio, and it can generate speech in a variety of languages.
LibriTTS:This TTS model is trained on a large dataset of audiobooks, and it can generate speech in a variety of languages.
Merlin:This TTS model is trained on a large dataset of text and audio, and it can generate speech in a variety of languages.
These are just a few examples of the many open source TTS models that are available. When choosing a TTS model, it is important to consider your specific needs, such as the type of voice you want to create and the languages you need to support.
Here are some of the benefits of using open source TTS models:
Cost:Open source TTS models are typically free to use, which can save you a lot of money if you are developing a commercial product.
Customization:Open source TTS models can be customized to meet your specific needs. For example, you can train an open source TTS model on a dataset of your own voice to create a voice that is truly unique to you.
Community support:Open source TTS models are often supported by a large community of developers who can help you with any problems you may encounter.
If you are looking for an open source TTS model, I recommend checking out the websites of the companies and projects listed above.
Codersarts AI: TTS-Based Services for Custom App Development
Codersarts AI offers a variety of TTS-based services, including:
App development:We can help you develop custom TTS-based apps for your specific needs.
Model training and deployment:We can help you train and deploy custom TTS models that can generate speech that sounds like you or your brand.
API integration:We can help you integrate TTS APIs into your existing applications.
PoCs, MVPs, and other demanding services:We can help you build PoCs, MVPs, and other demanding TTS-based solutions.
If you are interested in learning more about our TTS-based services, please contact us for a free consultation. React out to us via email@example.com
Client success story for a TTS-based app helped by Codersarts
Client: A large e-commerce company
Challenge: The company wanted to develop a TTS-based app that would allow customers to listen to product descriptions and customer reviews while shopping.
Solution: Codersarts AI developed a custom TTS-based app for the company that uses a state-of-the-art TTS model to generate natural-sounding speech. The app also includes a variety of features, such as the ability to save product descriptions and customer reviews for later listening, and the ability to adjust the speech rate and pitch.
Results: The app has been well-received by customers, and it has helped to increase sales and customer satisfaction. The company has also seen a reduction in the number of customer support tickets, as customers are now able to find the information they need more easily.
Client: A small educational startup
Challenge: The startup wanted to develop a TTS-based app that would help students with dyslexia learn to read.
Solution: Codersarts AI developed a custom TTS-based app for the startup that uses a special TTS model that is designed to generate speech that is easy for students with dyslexia to understand. The app also includes a variety of features, such as the ability to highlight words and phrases as they are spoken, and the ability to adjust the volume and pitch of the speech.
Results: The app has been very helpful for students with dyslexia, and it has helped to improve their reading skills. The startup has also seen a significant increase in demand for its app, and it is now used by schools and families all over the world.
These are just a few examples of how Codersarts AI has helped clients to develop anddeploy successful TTS-based apps. Codersarts AI has a team of experienced AI engineers who can help you to create a custom TTS-based solution that meets your specific needs.