What is Text-to-Talk?
Text-to-talk technology is software that converts digital text to a spoken conversation using a computer-generated voice. Organizations want to convert text to speech for various use cases, including education, customer interactions, assistive technology, digital avatars, gaming, automating routine phone calls, and more. Text-to-talk technology uses AI to convert written text into natural-sounding speech in the accent and dialect of your choice. AI voice generators can have very natural voice conversations with customers, including adding pauses, emotions, and varying speaking rates.
What are the benefits of text-to-talk?
Text-to-talk, or text-to-speech, allows organizations to engage with audiences using high-quality voices to narrate textual content. Below, we share key benefits the technology offers to businesses.
Improved accessibility
Companies can be more inclusive by leveraging text-to-speech technologies when producing content, particularly for people with visual impairments. Text-to-talk software turns content into an audio file, which people with reading difficulties can listen to.
Personalized engagement
With text-to-speech software, organizations can personalize audio content with the tone, voice, and style listeners enjoy listening to. Companies can deliver messages spoken in their custom brand voice to make a lasting impression.
Support learning activities
Text-to-talk allows organizations to explore new ways to support e-learning programs. By turning written content into audible forms, learners are more engaged and thus learn more effectively.
Increased audience reach
Some customers want more alternatives when accessing content online. Text-to-speech (TTS) allows organizations to make their content accessible to people who favor podcasts or videos over blogs and documents.
Provides an alternate learning method
Organizations can better support their employees' growth with text-to-speech training assistants. Instead of reading pages of text, they can listen to the content on the go and use their time more efficiently.
How did text-to-talk technology evolve?
Text-to-talk emerges as a measure to help Stephen Hawking converse verbally after the physicist lost his voice following a tracheotomy. The first text-to-talk system was invented by Dennis Klatt, which serves as the foundation of subsequent innovations in the field.
We share how several text-to-talk technologies have developed throughout the decades.
Formant synthesis
Formant synthesis is an audio technique mimicking a human’s voice by modeling the vocal tract. It is one of the earlier technologies that enabled text-to-speech systems.
Concatenation synthesis
Concatenation synthesis creates speech by combining multiple tiny blocks of sound recordings. It is a machine learning based text-to-talk development that gives standard results, but has now been superseded by deep learning and AI.
Deep learning based speech synthesis
Deep learning is an artificial intelligence method that teaches computers to make decisions in ways inspired by the human brain. By learning from curated audio data, it allows scientists to create speech synthesis that speaks more naturally.
Generative voice generator
Generative voice generators use generative AI to learn, improve, and produce realistic speeches. Like deep learning, generative AI trains with large volumes of audio data. Compared to earlier speech synthesis methods, generative voice generators produce speech audio with varying nuances like dialects, tones, . For example, Amazon Alexa is powered by generative AI, which allows for smarter, personalized, and more human-like conversations.
How does text-to-talk work?
A text-to-talk software interprets the text it receives and converts it into audio that people can listen to. However, the audio’s conversational quality depends on the underlying speech generation technology. There are four main types of text-to-speech technologies.
Standard engine
A standard engine uses concatenative synthesis to create natural speech. It combines parts of recorded sound stored in a database to form an entire spoken word. While the generated audio is clear and precise, it sounds more machine-like than natural. Standard engines are often used in IVR call menus where the recorded voice asks the user to enter options before transferring the call to the correct department.
Neural engine
Like the standard engine, the neural engine uses audio blocks as the foundation of speech synthesis. However, it doesn’t link those blocks together. Instead, it creates a continuous audio waveform by taking into account how different audio blocks would sound when put together. This allows the neural engine to produce natural-sounding voices.
Long-form engine
Powered by deeper learning technologies, the long-form engine can read out articles, books, newspapers, and other content with an emotionally adaptive voice. Through extensive learning, the engine produces audio similar to how people read aloud. When the engine receives a text, it interprets the meaning and chooses the appropriate tone, pauses, and accents. This results in a text-to-speech AI software capable of projecting human emotions.
Generative engine
The generative engine uses advanced AI algorithms to produce human-like speech. Machine learning engineers train the generative engine with audio data in multiple languages, voices, and styles. To produce speech, the AI software turns written text into speech codes and converts it into high-quality, continuous audio waveforms. A generative engine can observe and learn from digital interactions in real-time, allowing it to sound emotionally engaged, assertive, and highly colloquial, just like humans do.
What are key considerations when choosing text-to-talk technology?
You can find many paid and free text-to-speech platforms online. However, not all are designed to support flexible usage, customization, and other business needs. Below, we share points to consider when choosing a TTS solution.
Voice and language option
Some organizations serve customers in different regions. As such, they’ll need a text-to-speech software capable of creating speech in the local language, dialects, and voices.
Speech marks
Speech marks are special indicators in the generated audio that highlight the start and end of the spoken phrases. Speech marks are helpful if you want to pair the audio with visuals, such as an AI avatar. It allows the avatar to synchronize facial movement with the synthesized speech.
Speech configuration options
When working on commercial projects, you should experiment with various speech variations before getting the right fit. Some voice generators provide options that allow developers to adjust how the synthesized voice sounds, including:
- Speaking style
- Speech rate
- Pitch
- Loudness
- Speech duration
Speech synthesis via API
An application programming interface (API) allows software developers to introduce text-to-speech easily. Instead of building the speech synthesizer from scratch, they use an API to pass the text to the engine and receive the generated speech.
Custom vocabulary
Sometimes, text-to-talk software might not recognize or interpret certain words correctly. Usually, these words have non-standard spellings/pronunciations or are special terms used in specific industries. For example, receiver, when used in the context of electronics, points to hardware that detects incoming signals. By choosing a text-to-talk that supports custom vocabulary, you can include these terms so that the software can communicate more fluently with the users.
Proprietary customization
In some use cases, companies want to reflect their preferred voice style in the generated audio. To do that, you need a text-to-talk software to tailor to specific requirements, including tonality, nuances, and style unique to the brand.
How can AWS support your text-to-talk requirements?
Amazon Polly allows you to build text-to-speech applications that engage customers across regions and languages. With standard, long-form, generative AI and neural engines, you can convert any document type to speech as needed.
You can use Amazon Polly to
- Choose from dozens of readymade voices across languages, dialects, and genders.
- Include or modify rare vocabulary, such as company names, foreign phrases, or industrial terms.
- Stream the generated audio in real time with various sampling rates and formats.
Companies use Amazon Polly to augment their applications with natural-sounding voices without investing in expensive technologies.
Get started with text-to-talk by creating a free AWS account today.