What Is Neural TTS? Features, Possibilities & 4 Best Neural TTS Apps

Interested in the latest advancements in text-to-speech technology? Know Neural TTS and explore the top apps making waves in the industry.

AI mind with neurons - Neural TTS

Neural TTS, short for Neural Text to Speech Technology, is revolutionizing the way we interact with machines and voice assistants. The ability to generate human-like speech patterns from text opens up a world of possibilities in terms of accessibility and user experience. Neural TTS can make the listening experience smoother, more natural, and emotionally engaging. This blog aims to explore the technology's benefits and the challenges to its widespread adoption.

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Evolution Of Neural Text To Speech

Evolution of Neural TTS

The journey from traditional text-to-speech (TTS) systems to neural TTS has been nothing short of revolutionary. Originally, TTS systems struggled to produce natural and emotionally rich speech. With the introduction of deep neural networks and vast speech datasets, neural TTS systems have made significant strides in generating more lifelike speech.

Advancing Speech Synthesis Technology

The WaveNet technology, developed in 2016, by the London-based firm DeepMind, marked a turning point in this evolution by using neural networks trained on genuine speech recordings to produce speech that almost mimics human speech patterns.

​​Replicating Human-Like Speech Patterns

The integration of neural networks with machine learning has resulted in a phenomenal improvement in the responsiveness and authenticity of computer-generated speech. By learning the intricate intricacies of human speech from scratch, neural TTS systems have achieved remarkable success in replicating human-like speech patterns.

What Is Neural TTS?

definition of Neural TTS

Neural TTS and the Advancement of Synthetic Speech Quality

I have spent a considerable amount of time studying and advancing my knowledge of neural TTS systems within the realms of speech synthesis. Neural TTS is a technology that employs artificial neural networks to create human-sounding speech from text. This type of speech synthesis has the potential to revolutionize the way we interact with technology by providing a more natural and expressive form of communication.

Mimicking Human Speech

Neural networks are utilized in this system to enhance speech quality and make it sound more human-like. They operate similarly to the human brain through the complex webs of electrochemical connections between nerve cells. As these connections develop through repetition and practice, they require less effort to activate – making the processes more efficient over time.

Neural Networks in Speech Synthesis

I have come to understand that the use of neural networks in the development of natural-sounding speech is pivotal. These networks are clusters of processing units that are akin to artificial neurons. They serve the function of classifying input data and transmitting it to other artificial neurons. By defining parameters for the desired results and processing large datasets, neural networks learn to map optimal paths from neuron to neuron and from input to output.

Evolution from Robotic to Human-Like Speech

In the past, traditional TTS systems could easily be recognized due to their robotic and monotonous speech. With the progression of neural voices, there have been significant improvements in the quality and naturalness of synthetic speech. Nowadays, we are witnessing a more human-like quality that has been achieved through recent advancements in neural TTS technology.

Components of Natural-Sounding Speech

The creation of a neural TTS system that closely resembles the human voice necessitates access to multiple deep neural network models such as the acoustic, pitch, and duration models. These models each play a crucial role in enhancing the final output, resulting in speech that is more natural and expressive, suitable for a wide array of applications like virtual assistants, audiobooks, and language learning tools, among others.

Neural Text To Speech Models

woman working with Neural TTS

To create a neural TTS voice, DNN models are trained on recordings of human speech. The resulting synthetic voice will sound like the input data which is the source speaker, which is why neural TTS voice is also referred to as voice cloning. This imitation process takes a lot to pull off and DNN TTS voices require at least three distinct neural models, which combine to recreate the voice:

  • The acoustic model reproduces the timbre of the speaker’s voice, the color or texture that listeners identify as belonging to that speaker
  • The pitch model predicts the range of tones in the speech, not just how high or low the TTS voice will be, but also the variance in tone from one phoneme to the next
  • The duration model predicts how long the voice should hold each phoneme. It helps the TTS engine pronounce the word “speech” rather than “sspeeech,” for instance.

The latter two models are considered prosodic parameters. That’s because they determine prosody, or non-phonetic properties of speech like intonation, rhythm, and breaks. Meanwhile, the acoustic model predicts acoustic parameters that capture information about the speaker’s voice timbre and the phonetic properties of speech.

Key Features And Possibilities Of Neural TTS That Make It Better Than Traditional TTS

man in a special environment - Neural TTS

One of the most exciting possibilities of Neural TTS is the capability for prosody transfer. This feature allows for the transfer of prosodic features such as stress, emphasis, intonation, and rhythm from one voice to another. This enables more control and customization of synthesized speech, resulting in more natural and human-like speech. This feature is particularly beneficial for voice-based applications like voice assistants.

Speaker Adapted Models

Another significant feature of Neural TTS is the ability to create speaker-adapted models. These models use deep neural networks to learn the relationship between text and speech from specific data, including the unique characteristics of a speaker's voice. As a result, these models can be adapted to produce speech in the voice of a particular speaker with minimal training data.

Emotional Speaking Styles

Neural TTS also offers the possibility of creating emotional speaking styles, adding expressiveness and believability to synthesized voices. Unlike traditional TTS systems, which may struggle to produce emotionally expressive speech, Neural TTS models can be trained to produce audio in different emotional tones such as happy, sad, or angry. This feature enhances the adaptability of AI speakers to various contexts and applications.

4 Best TTS Apps Using Neural TTS

team using Neural TTS

1. Unrealspeech: A Cost-Effective Neural TTS Solution

Unrealspeech offers a low-cost, scalable text-to-speech API with natural-sounding AI voices. This platform is known for its cost-effectiveness, providing a solution that cuts up to 90% of text-to-speech costs with human-like AI voices. The API ensures super fast and low latency performance, with the option for per-word timestamps. The service also offers a simple and easy-to-use API, allowing for the seamless integration of text-to-speech functionality at scale.

2. Amazon Polly: A Comprehensive Neural TTS Service

Amazon Polly is a cloud-based text-to-speech service that boasts over 90 natural-sounding voices across 34 languages and dialects. The platform's neural text-to-speech technology is a standout feature, providing high-quality voice options for users across multiple languages and regions.

3. Speechify: Advanced Neural TTS Features

Speechify is a text-to-speech software equipped with several advanced features, including OCR scanning, voice customization, and instant translation. This innovative tool offers a wide selection of over 130 high-quality voices that closely resemble human voices, enhancing the overall user experience.

4. NaturalReader: Diverse Neural TTS Capabilities

NaturalReader is a text-to-speech software packed with various features such as pronunciation customization, voice style selection, and OCR capabilities. The tool boasts over 150 natural-sounding voices across more than 20 languages, ensuring a diverse range of options for users seeking high-quality neural text-to-speech services.

Try Unreal Speech for Free Today — Affordably and Scalably Convert Text into Natural-Sounding Speech with Our Text-to-Speech API

Unreal Speech offers a groundbreaking text-to-speech API powered by Neural TTS technology. This cutting-edge approach to converting text into speech brings a host of benefits and advantages to developers and businesses. With Unreal Speech, you gain access to an affordable and scalable solution that provides high-quality, natural-sounding AI voices.

Neural TTS on Speech Realism

Neural TTS technology has revolutionized the field of TTS by significantly improving the realism and naturalness of synthesized speech. This breakthrough innovation allows Unreal Speech to deliver AI voices that sound remarkably human-like, providing an engaging and immersive experience for users.

Leveraging Neural TTS for Enhanced User Experience

The key advantage of Neural TTS technology is its ability to produce speech that closely mimics the cadence, tone, and inflection of human speech. This level of realism enhances the overall user experience, making interactions with AI-driven applications more intuitive and compelling. By leveraging Neural TTS technology, Unreal Speech sets itself apart as a leader in providing low-cost, highly scalable TTS solutions.

Real-Time Speech Synthesis with Unreal Speech's API

Unreal Speech's API offers lightning-fast performance and low latency, ensuring that your applications can generate speech on the fly without any noticeable delays. This real-time functionality is crucial for applications that require instant speech synthesis, such as conversational AI agents and virtual assistants.

By incorporating Neural TTS technology into your products and services with Unreal Speech, you can offer your users a premium TTS experience at a fraction of the cost of traditional solutions. Whether you're developing a chatbot, virtual tutor, or accessibility tool, Unreal Speech's text-to-speech API can help you deliver a more engaging and accessible user experience.