Speech-to-Text (STT) and Text-to-Speech (TTS) solutions are technologies that rely on machine learning to translate data from an audio form to a written form, or from a written form to an audio form. These solutions are also commonly referred to as “Read Aloud” technologies.
This has a wealth of applications for both individuals and enterprise teams. They can help make applications and content more accessible, generate voiceovers and podcasts, enable corporate and HR meetings to be automatically written into clear and legible notes, and aid writers and journalists in editing articles and creating transcripts.
These solutions have become increasingly useful as the technology has improved over time. Speech-to-text solutions have become far more accurate, and text-to-speech solutions have become more human-like, with the ability to differentiate between tones and control pitch. Both services have become far more adept at managing multiple languages and accents.
Here’s our list of the top 10 AI text-to-speech and speech-to-text solutions, based on features offered, investment raised, and which teams they are best suited for.
How Do AI Text-To-Speech And Speech-To-Text Work?
Text-to-speech (TTS) solutions utilize AI systems with natural language processing capabilities. This means they can analyze and synthesize human speech patterns and linguistics. When the AI system is fed a chunk of text, it can use audio data to generate a voice that sounds human, “reading” the text aloud for a human audience.
Speech-to-text (STT) solutions on the other hand, work in the opposite direction. This software listens to audio and delivers a transcript of the words heard, aiming to be as accurate and legible as possible.
STT picks up on vibrations made when humans speak and translates this into a digital language. This is then analyzed to distinguish relevant sounds and matched to phonemes, which helps the AI to identify the particular words used. This is then further analyzed using ML models to compare these words to well-known sentences and phrases, which are then displayed to the end user, as accurately as possible.
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