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The Technology Behind Custom Text-to-Speech

Image by Kaufdex from Pixabay

Text-to-speech (TTS) technology is becoming a modern-day commodity. With millions of people using voice search every day, it is safe to say that it is the right time to learn about TTS.

What is more, we are living in the so-called “digital era.” These new times we live in can be both exciting and confusing; some people find it more challenging to embrace modern technology than others and might be uncomfortable using text-to-speech software.

However, thanks to the development of speech synthesis software, it is now much more frequently used.

The best way to get to grips with this useful new technology is to dive in the deep end and use tools that produce synthesized voice more often and learn about them.

If you feel like text-to-speech is your weak point, do not worry! We are here to help you. In this article, you will gain access to useful information on text-to-speech technology.

Understanding the Process

Text-to-speech is an outstanding achievement in the field of computer science. It can benefit people who have difficulty reading text on their computer screens or other devices. It can also be convenient if you want a text read to you, for instance, when you are driving.

Notable examples of successful speech synthesis users include renowned physicist Stephen Hawking and former NFL player Tim Shaw. And they are not the only ones who benefited from using this technology.

A working text-to-speech system is composed of two parts. One of them is a front-end, and the other is a back-end; they are both responsible for different tasks.

The former is tasked with converting raw text into the equivalent of written-out words. What is more, it is also responsible for phonetic transcriptions of every word. On the other hand, the latter converts the symbolic linguistic representation into audio.

A typical TTS process can be divided into three phases: gaining input, processing the collected information, and producing the output. However, if you look close enough, you will see that there is much more to the process.

Step 1: Converting Voice Into Data

To create human-like sounding speech Artificial Intelligence (AI) first needs to gain some information. It needs some audio samples that it can use later to learn.

For example, if we would like our text-to-speech system to operate in English, we need to provide some text and audio samples in this language of our choice.

Thanks to automatic speech recognition (ASR), AI changes the voice it hears into language data it can work on later. The quality of the samples is of utmost importance.

This step usually requires building a vast database of recorded human speech. However, speech recognition software can even enable our virtual assistants to hold conversations with us! How is that done? This question leads us to the next step.

Step 2: Understanding the Data

After gaining some input, now comes the time to read the text and derive meaning from the words. When the sound has been processed to something the AI can work on, it reads the content in its digital database.

Virtual assistants do not only read the language samples they are provided with. The machine is learning how to use them correctly as well.

It uses its neural networks to make sentences that will make sense. The result of this is based on the quality of the content it was previously given.

AI is tasked with understanding how we use words. It needs to know what one speaker says to the other and the typical answer. It is fascinating to know that neural networks the AI is based on can even produce some original and spontaneous reactions!

Step 3: Producing the Output

Converting standard language text into speech is what happens at the core of this step. Now the AI is tasked with producing audio that can be interpreted as a natural sounding voice.

This step involves converting language characters into phonemes. The real challenge here is the correct reading aloud of the text. The context of the situation should also not be omitted.

It is the final step of speech synthesis. Every word that the machine uses has gone through the reading and learning phase.

Summary

Now you know how text-to-speech technology works. As you can see, it requires many hours of learning and vast amounts of resources. Nonetheless, this technology is becoming more accessible by the day!

Maybe soon we will hold some fascinating conversations with applications on our devices? In a matter of a few years, every machine may pass the Turing test! Such a breakthrough could revolutionize our lives.

Devices with TTS can become great support tools for many people. We can make use of their service right now! For example, Amazon has Alexa and Google provides its users with Google Assistant.

Text-to-speech technology improves the lives of many sight-impaired people and is a convenient alternative way of absorbing text for others. Hopefully, in the future, the features of machines based on TTS will be accessible for all.

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