What is the history of text to speech and voice synthesis?

What Is the History of Text to Speech and Voice Synthesis? Uncover the breakthrough moments and key players behind voice synthesis and text to speech technology.

Text to speech (TTS) and voice synthesis might seem like brand-new technologies, but they actually have a rich history that goes back centuries.

From the earliest attempts to mimic human speech using mechanical devices to today's cutting-edge artificial intelligence and deep learning models, the development of TTS has been a fascinating journey.

In this article, we'll take a deep dive into the history of text to speech and voice synthesis and explore the exciting possibilities for the future.

Text to speech and voice synthesis: from early development to modern-day use

18th and 19th century

The history of text to speech and voice synthesis can be traced back to the 18th and 19th centuries. During this period, there were several early attempts at speech synthesis, all using mechanical devices. In the 1770s, Wolfgang von Kempelen, a Hungarian inventor, developed a mechanical device called the acoustic-mechanical speech machine designed to simulate the human vocal tract. This analog device used bellows, reeds, and pipes to produce vowel and consonant sounds.

In the late 18th century, an English physicist, Charles Wheatstone, invented a more mechanical version of Kempelen's speech machine, which he called the "speaking machine." The device could reproduce the sounds of various musical instruments. Although Wheatstone's device wasn't explicitly designed for speech synthesis, it reinforced the idea of using a mechanical device to produce sound.

In the 19th century, various other devices were developed, including Faber's "artificial speech" machine. These devices used a combination of mechanical and pneumatic systems to create speech sounds.

Early 20th century and the first fully-electrical speech synthesis

In the early 20th century, speech synthesis technology became more sophisticated with the invention of the first fully-electrical speech synthesis system – the vocoder by Homer Dudley. The system was developed at Bell Laboratories (Bell Labs) in New Jersey.

Dudley's vocoder used a series of resonators and filters to create synthetic speech. Experts showcased the vocoder, called the Voder, during the 1939-1940 World's Fair in Flushing Meadows, New York. They operated the machine using a keyboard and foot pedals to generate speech.

Early 1950s to late 1970s – the rise of synthesizers

In 1951, Dudley's work inspired the development of the pattern playback by Dr. Franklin S. Cooper at Haskins Laboratories. The system worked by analyzing a recorded sound, such as a spoken word or phrase, and breaking it down into its component sound waves or "spectrographic patterns." These patterns were then stored on magnetic tape and played back to produce a synthetic version of the original sound.

In 1976, the first commercially successful text to speech system was introduced by Kurzweil Reading Machine. The system used a concatenative synthesis technique, combining pre-recorded phonemes and words to produce synthetic speech. The device was primarily designed to assist individuals with disabilities, but it quickly gained popularity as a reading aid.

Beginning in 1978, Texas Instruments started working on a speech synthesis chip that could be used in video games and other computer-based applications. The chip used concatenative synthesis, which combined recorded speech sounds, or diphones, to produce human-like speech output. This technology was later used in the DECtalk, a text to speech system that provided high-quality synthetic speech for people with disabilities.

Modern text to speech systems

One of the key innovations in recent years has been the use of neural networks to generate synthetic speech. Companies like Google and Microsoft have developed high-quality TTS systems that use deep learning algorithms to analyze large datasets of human voices and generate natural-sounding speech output.

Another critical development in TTS as a form of assistive technology has been the use of unit selection and concatenative synthesis techniques. These methods allow for more realistic outputs by combining small units of pre-recorded speech, such as diphones or even entire words, to create new sentences. These techniques have been used in popular TTS apps like Speechify, Apple's Siri, and Amazon's Alexa, as well as in older tools like IBM ViaVoice.

Speech recognition technology has also advanced significantly in recent years, which has allowed for more sophisticated TTS systems. Using speech recognition algorithms to transcribe human speech into text, TTS systems can create more natural transitions in synthesized speech.

In recent years, we've also seen the integration of prosody and intonation. This allows for more natural-sounding speech, with appropriate pauses, emphasis, and tone. Prosody is especially important for languages like English, where stress and intonation can significantly affect the meaning of a sentence.

Deep learning and beyond: the future of technology

The future of TTS technology is exciting and full of promise. With the rise of artificial intelligence and deep learning, we can expect even more natural-sounding speech output that can mimic the subtleties and nuances of human speech.

One area where this will be particularly useful is the development of virtual assistants and chatbots. These systems will become more conversational, and users will be able to interact with them in a more natural way.

In addition, we can expect advancements in the field of phonetic transcription, also known as text-to-phoneme conversion. As machines become better at recognizing and interpreting human speech, the accuracy and efficiency of speech-to-text systems will continue to improve.

Finally, we can expect text to speech technology to become more widely available and integrated into our everyday lives. As more devices become connected to the Internet of Things, we will be able to control them with our voices in real time, making our lives more convenient and efficient.

Join the text to speech revolution with Speechify

If you're looking for a powerful text to speech service that can produce natural, high-quality narration, look no further than Speechify.

With its advanced formant synthesis technology, Speechify creates realistic, natural-sounding voices, unlike the robotic voices of the past. Even acclaimed writers like Stephen Hawking – who once tried his hand in text to speech technology – would be impressed by Speechify's capabilities.

Using Speechify is easy – simply visit the official website or download the mobile app and enter your desired text. Next, choose a voice that suits your needs, adjust the speed and pitch as needed, and voila! Speechify will create excellent and natural-sounding narration perfect for e-learning modules, explainer videos, podcasts, and presentations. You can even create your own custom voices for use on YouTube and other social media channels.

Don't settle for inferior TTS services – give Speechify a try today and experience the future of text-to-speech technology.

FAQ

Who developed the world's first speech synthesizer?

Homer Dudley designed the world's first speech synthesizer in the early 1930s at Bell Laboratories in New York.

What is the purpose of speech synthesis?

Speech synthesis aims to generate artificial speech from text input using language processing and fundamental frequency analysis.

What are the four ways TTS can be used?

TTS can be used for accessibility, entertainment, language learning, and automation of voice-based services.

What are some of the advantages of text to speech?

Text to speech can improve accessibility, enhance learning, and increase productivity by allowing users to consume written content in an auditory format.

What has been the most surprising moment in the development of text-to-speech synthesis?

One of the most surprising moments in the development of text to speech synthesis was the invention of Charles Wheatstone's mechanical speech synthesizer.