Neural text to speech has changed TTS technology forever. Here’s everything you need to know about it, including where to find it for personal use.

What is neural text to speech?

Speech is a complex form of communication. Besides conveying meaning, your words are influenced by context and filled with emotions. For this reason, reproducing the subtleties of spoken language might seem beyond the capabilities of a machine. However, with recent advances in text to speech (TTS) technologies, machines have never been closer to sounding like humans. Ending the decade-long quest to generate natural speech, researchers from London-based firm DeepMind developed the WaveNet technology in 2016. This technology uses neural networks trained on authentic speech recordings to generate near-human speech. Combining neural networks with machine learning led to the advent of neural TTS, which has dramatically improved the responsiveness and authenticity of computerized speech. This article covers everything you need to know about this innovative technology and how to get your hands on it.

What is neural text to speech?

Neural TTS is text to speech powered by artificial intelligence and deep learning. As a result, neural speech synthesis is significantly more natural and expressive than standard text to speech synthesis. Neural TTS is still a form of machine speech—only it’s built with neural networks modeled on the human brain. Like the brain, these systems employ incredibly complex webs of electrochemical connections to process data. New pathways form through repetition, thus requiring less effort to activate the next time. Neural networks used for neural TTS process large datasets to learn the optimal pathways from input to output. This is a form of machine learning since these networks use a neural vocoder to synthesize speech waveforms without user input. For a neural TTS system to closely imitate the human voice, it requires access to multiple deep neural network models. These models include the acoustic, pitch, and duration models. The latter two models are considered prosodic parameters since they dictate the non-phonetic speech properties like intonation and rhythm. These properties are known as prosody. As for the acoustic features, they dictate the energy and pitch of a spectrogram. So far, there have been several neural models that have revolutionized text to speech technology.

• WaveNet: an autoregressive model using a fully convolutional neural network
• Deep Voice: a complex model consisting of four neural networks forming an end-to-pipeline heavily focusing on phonemes
• Tacotron: the first end-to-end model following the familiar encoder-decoder architecture

These models were later replaced by new and improved versions, including:

• Deep Voice 2
• Deep Voice 3
• Parallel WaveNet
• Tacotron 2

New transformers-based models have appeared in recent years, aiming to tackle issues of previous TTS models.

What can you use text to speech for?

Text to speech (TTS) technology has a wide array of applications that serve to enhance communication, accessibility, and convenience across various domains. In the educational sector, TTS aids learners with reading difficulties or visual impairments by converting digital text into spoken words, ensuring content is accessible to all. Audiobook production has become more efficient with TTS, allowing for rapid conversion of text-based content into auditory formats. For the visually impaired, TTS facilitates everyday tasks, from reading emails to navigating websites. However, you don’t need to have a disability in order to benefit from text to speech. Everyone can enjoy TTS apps to boost productivity, help with multitasking, or just give your eyes a break. In transportation, GPS devices utilize TTS to provide spoken directions, ensuring drivers can keep their eyes on the road. Additionally, businesses use TTS for automated customer service phone lines, while developers integrate it into virtual assistants and smart home devices. Its adaptability and evolving quality make text to speech an indispensable tool in a myriad of modern applications.

What are the best apps using neural text to speech?

Now that you’ve learned what neural TTS is, let’s see how you can enjoy the benefits of this innovative technology. Here are the top three TTS apps with the most natural-sounding voices.

Amazon Polly

Amazon Polly is a cloud-based text to speech service that offers over 90 natural-sounding voices across 34 languages and dialects. Neural text to speech technology is one of the platform’s most significant selling points. As a web-based console, Amazon Polly can be used across multiple platforms, including iOS and Android devices. It’s also available as an API for integration into third-party applications.

NaturalReader

NaturalReader is a text to speech software tool with various features, including pronunciation customization, voice style selection, and OCR capabilities. The tool offers over 150 natural-sounding voices across more than 20 languages. You can download NaturalReader to Windows and Mac computers and iOS and Android devices.

Speechify

Speechify is the best TTS option on this list, and it is a text to speech software tool with numerous advanced features—including OCR scanning, voice customization, and instant translation. This innovative tool features over 130 high-quality voices that uncannily resemble human voices. Plus, there are over 30 languages and dialects, including Spanish, Japanese, and Chinese. Part of what makes Speechify the best choice is how realistic its text to speech with emotion is compared to other TTS software. Speechify is available across all major devices. You can download a mobile app for iOS and Android devices, a desktop app for Mac and Windows computers, or a web-based version for any web browser.

Speechify—A treasure trove of natural, human voices

Thanks to Speechify’s versatility, it has quickly become one of the leading TTS software tools on the market. Speechify offers a high degree of customization, from the reading speed to the selected voices, which few other TTS platforms can boast. It also offers an impressive number of integrations, including API. Thanks to a dedicated app for each platform, Speechify users have a seamless experience every time. Throw the high quality of Speechify’s voices into the mix, and it becomes clear why this tool has been the go-to choice for millions of users worldwide. Download Speechify for free today and hear how natural the platform’s voices sound firsthand.

FAQ

Is there a text to speech that sounds natural?

Yes, there is a text to speech that sounds natural. It’s called neural TTS.

What is the most natural voice text to speech?

Speechify features some of the most natural voices on a text to speech software tool.

What are the benefits of neural text to speech?

Voices produced by a neural text to speech system sound much more natural than most regular TTS voices. They are also highly adaptable and can easily switch between speaking styles.

What is the difference between text to speech and audio to speech?

Text to speech tools convert text into spoken word. As such, you need to input text for these tools to work. In contrast, audio to speech tools use speech recognition to respond to speech adequately in real time. These tools are known as virtual assistants, with Google’s Alexa, Apple’s Siri, and Microsoft’s Cortana being the most prominent examples.

Does neural text to speech sound natural?

Yes, neural text to speech sounds remarkably natural. It is based on recurrent neural networks, thus producing incredibly human-sounding synthesized speech and natural language.

Can neural TTS create custom voices?

Yes, Neural TTS can be used to craft custom voices that fit numerous use cases, from screen readers to customer support chatbots, for a seamless customer experience. Azure is among the most prominent manufacturers of these voices, offering complete control over speech parameters thanks to Synthesis Markup Language (SSML), and a testing toolkit.