The path to AI voice generation started in the early 1960s when the first voice synthesizer was introduced, followed by the launch of the first text-to-speech program. More affordable and accessible text-to-speech software was launched in the 1980s and 1990s.
Thanks to the advent of machine learning and AI modeling, modern voice generators are much more powerful, synthesizing realistic voice patterns including inflections, emotions, and even sarcasm. AI voices are almost indiscernible from real human voices, and the technology is only improving.
What Are AI Voice Generators?
AI voice generators are pieces of software that read text or replicate audio data to create speech. The use of machine learning, text-to-speech technology, and text analyses produces realistic results with AI that speaks like you. According to technology writer, Alice Martin, the software can be useful for the creation of voiceovers, for narrating audiobooks, or even for audio chatbots.
How Do They Work?
From the end user’s point of view, AI voice generators work by providing some kind of input, altering the voice characteristics, and having the AI generate speech patterns based on those parameters. The input can be text or audio-based. The AI can be given blocks of text to read or repeat verbatim, or it can be used more conversationally, answering questions using AI prompts.
Although different generators use different specific techniques, they all use the same basic techniques.
Deep Learning Algorithms
Deep learning is a type of machine learning that uses neural networks to analyze and learn from huge amounts of data. In the case of voice generators, they initially use large databases of spoken words. The software analyses different ways and pronunciations of as many words as possible.
As with any data analysis, the larger the data set, the more the software can learn and, ultimately, the more realistic the resulting voice will be when it is spoken. Voice data examples can include audio books, TV programs, and a database of individual words created specifically to train AI models.
Text Analysis
AI first breaks words down phonetically into their constituent parts. The software then determines things like the subject of the phrase before categorizing and translating the words based on their context. With large volumes of data, AI software can learn how people tend to speak phrases of words together, rather than individual words.
Reading words out individually is what leads to robotic-sounding speech, rather than human-like prose.
Text To Speech Technology
Text-to-speech technology has existed for decades, although it is only in the past couple of decades it has become so affordable. Originally used for accessibility and to help children learn to talk and read, text-to-speech has become popular in video, social media design, and media production.
Even basic text-to-speech software has improved so it doesn’t sound so robotic. However, AI-based speech generation software is even more advanced as it uses the same intonations, stresses, and other voice characteristics of real people.
Voice Synthesis
Once AI has a good understanding of language and individual words, it needs to be able to convert these words into speech.
Lifelike voice synthesis attempts to accurately replicate human speech, making it indiscernible from the way we speak to one another. It uses emphasis, intonation, and other human vocal characteristics to be as realistic as possible.
Natural Language Processing
We all speak slightly differently. We deaden some letters and pronounce others more markedly. We have accents and we convey feelings and emotions, especially when we are talking about certain topics. While analyzing language, the software needs to be able to process all of these different voices.
When asked to speak, AI needs to analyze what it is going to say to determine an appropriate voice. It then needs to use natural-sounding responses, which not only means constructing an appropriate sentence but also using a lifelike voice.
User Preferences
As well as a natural-sounding voice, AI voice generators can be altered according to user preferences. At the most basic, the user can determine whether they want a feminine or masculine voice and whether the voice should sound old or young. But, it is also possible to change parameters such as accent, mood, speed of speech, and tendency to use certain words or phrases.
Should the voice use wordy sentences or briefer responses? Should it be sarcastic, jovial, or serious? AI voice generators can be customized with these and other specific choices.
Constant Learning
The most powerful AI continues to adapt as it learns. AI voice generators can hold conversations with people and they can be provided with additional data. As it learns, the AI should continue to further improve all elements of its voice generation.
In particular, AI companies will encourage and even incentivize user feedback. They can use this feedback to learn what needs improving and what the voice generator is doing well. This means that the results will continue to improve over time.
AI Voice Generator Uses
AI voice generators are still relatively new. Text-to-speech software has been used for everything from video voiceovers to improving accessibility via screen readers and other functional uses. AI voice generators can enjoy some of these same uses, but their increased intelligence means they have an even broader scope.
- Voiceovers – Videos, slideshows, and other marketing materials can help drive new business. But they can cost a lot of money, especially when hiring voiceover narrators. Realistic AI voice generators continue to improve and are already at a level where it is difficult to differentiate AI from human voices. They can be used as a cost-effective tool for video and audio voiceovers.
- Narration – Audiobook narrators can earn hundreds of dollars an hour to narrate hundreds of pages of text. As such, it can cost thousands of dollars to narrate a single book. For best-selling titles, it is feasible to spend this amount of money. But, for first-time publishers and self-publishers, it is a cost that few can really afford. AI voice generation is a lot cheaper than even paying novice or first-time narrators.
- Media – There has been a lot of controversy surrounding the use of generative AI in the media industry. But where AI can be used is to narrate films or create voiceovers for animated films. There will come a time when AI actors are used in some productions, not just their voices, but for now AI voices are becoming increasingly common thanks to their realism.
- Chatbots – Chatbots are good communication and marketing tools. They can be used to direct customers to relevant pages on websites. Or they can advise the best products or services to buy, answer customer queries, and more. While chatbots are commonly text-based responders, voice generation means that they can now answer calls and provide vocal responses over the phone. Some hotels even have AI concierges which are basically advanced chatbots.
Conclusion
AI is more advanced than ever, using machine learning algorithms to be more convincingly human. One area where it has become especially advanced is in voice generation, and the technology continues to improve further. Many of us may be hearing AI-generated voiceovers on content videos, and even while listening to audiobooks, and it likely won’t be long before we hear it on TV and in movies.
