This makes developing new, smart ReadSpeaker TTS voices with even more lifelike, expressive speech and customizable intonation faster than ever. Also, the resulting speech is generally smoother and even more human-like. Only a few hours of recorded speech are needed for a neural voice, compared to at least three times as many for a good quality USS voice. One of the advantages of the new DNN TTS method is that the acoustic database can be much smaller than for a USS voice. An iterative learning process minimises objectively measurable differences between the predicted acoustic features and the observed acoustic features in the training set. This revolutionary method involves mapping linguistic properties to acoustic features using Deep Neural Networks (DNNs). In parallel, ReadSpeaker creates so-called neural voices, using techniques based on deep learning AI technology. Through a system of high-quality feedback and a thorough Quality Assurance process by mother-tongue experts, imperfections are continuously corrected. One of ReadSpeaker’s unique characteristics is our ongoing improvement process. This is how a new ReadSpeaker TTS voice persona is born. The resulting database is used by the ReadSpeaker TTS engine to convert text into speech spoken by the TTS voice: segments (units) of speech are selected and ‘glued’ together in such a way that high-quality synthetic speech is produced. Our state-of-the-art methodologies are augmented by the linguistic expertise of our team. The technical team works its magic on this process – using a powerful combination of Artificial Intelligence and machine learning technologies on big amounts of data to optimize annotations. To create a USS voice, the audio resulting from recording the voice talent is segmented into smaller units, such as sentences, words, syllables, phonemes (speech sounds such as individual vowel and consonant sounds).Ī rich mark-up is added to this database of speech units, which is to say information is added to the units about the stress (did the unit come from a stressed or from an unstressed syllable?), the position in the word or sentence, etc. These voices are still used in most of our SaaS solutions, such as webReader and docReader. Until about 2019, all our high quality voices were made using a technology called Unit Selection Synthesis (USS).
The team closely monitors the recording process to check for consistency in pronunciation, accentuation, and style. A diverse script is used for the recordings, designed to contain all the sound patterns of the language in development. Once a voice talent has been selected, she or he works with our voice development team for several days or weeks, depending on the type of voice, or the voice technology, we want to use.
#Meme text to speech voices professional
To create our speech personas, we select and record professional voice talents. Our commitment to providing outstanding TTS solutions is made possible by our uncompromising production process, designed to guarantee the quality levels that have earned ReadSpeaker TTS the trust of customers from across countries and markets. The enthusiastic feedback we receive from our customers confirms that we deliver the very best TTS solutions for successful online, offline, embedded, and server-based applications around the world.
In fact, expert third party industry observers rate the US English ReadSpeaker TTS voice as being the most accurate on the market.
At ReadSpeaker, we have a passion for developing high-quality TTS voices.
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