![]() 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). ReadSpeaker creates so-called neural voices, using techniques based on deep learning AI technology. 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. 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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