Go to Menu Search on ReadSpeaker.com

ReadSpeaker TTS Voices

Discover the ReadSpeaker TTS voice portfolio, recognized as one of the most accurate and lifelike on the market, or ask us about custom voices.

Contact Us

Listen to a Custom Text Read Out by Any of Our TTS Voices

This demo tool lets you enter your own text and sample some of the languages and voices that we offer.
Please note:  Not all languages and voices are available for every solution. Also, more voices are available for certain solutions. See our Languages & Voices page for a complete list of available languages for each solution.

Loading
There was an error, please try again.

Terms of Service - This demo is for evaluation purposes only; commercial use is strictly forbidden. No static audio files may be produced, downloaded, or distributed.The background music in the voice demo is not included with the purchased product.

none Lene Danish Female
taiwanese Yafang Chinese Female
none Somsi Thai Female
none Sarawut Thai Male
none Aleksei Russian Male
none Vera Russian Female
none Tiago Portuguese Male
none Carolina Portuguese Female
none Lykke Norwegian Female
none Elina Finnish Female
australian Mia English Female
none Simona Slovak Female
none Jakub Slovak Male
none Annisa Indonesian Female
none Bayu Indonesian Male
none Teodor Romanian Male
none Veerle Flemish Female
none Amir Arabic Male
american Sophie English Female
american Kate English Female
american Julie English Female
american Ashley English Female
american Beth English Female
american Mark English Male
american James English Male
american Paul English Male
australian Jack English Male
australian Mason English Male
mandarin Hong Chinese Female
mandarin Hong Chinese Female
canadian Chloe French Female
canadian Leo French Male
brazilian Helena Portuguese Female
brazilian Rafael Portuguese Male
british Hugh English Male
none Ilse Dutch Female
none Anne Dutch Female
none Guus Dutch Male
none Alex Dutch Male
mandarin Hong Chinese Female
mandarin Hui Chinese Female
mandarin Qiang Chinese Male
mandarin Liang Chinese Male
none Benoit French Male
none Louis French Male
british Bridget English Female
british Alice English Female
none Lena German Female
none Max German Male
none Tim German Male
none Elise French Female
none Roxane French Female
mexican Francisco Spanish Male
none Hyeryun Korean Female
none Yumi Korean Female
none Jihun Korean Male
none Junwoo Korean Male
none Show Japanese Male
none Ryo Japanese Male
none Akira Japanese Male
none Gina Italian Female
none Elisa Italian Female
none Roberto Italian Male
none Ania Polish Female
mexican Violeta Spanish Female
mexican Gloria Spanish Female
none Sayaka Japanese Female
none Risa Japanese Female
none Misaki Japanese Female
none Hikari Japanese Female
none Manuel Spanish Male
none Adina Romanian Female
none Maja Swedish Female
none Karin Swedish Female
none Sven Swedish Male
none Pilar Spanish Female
none Lola Spanish Female
none Oskars Latvian Male

ReadSpeaker text-to-speech voices are humanlike, relatable voices. There are 110+ voices available in 35+ languages, with more on their way. Meet the ReadSpeaker TTS family of high-quality voice personas and put them to the test.

Industry-Leading TTS Voices

At ReadSpeaker, we have a passion for developing high-quality TTS voices. In fact, expert third party industry observers rate the US English ReadSpeaker TTS voice as being the most accurate on the market. 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. 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.

How Our TTS Voices Are Made

To create our speech personas, we select and record professional voice talents. 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. A diverse script is used for the recordings, designed to contain all the sound patterns of the language in development. The team closely monitors the recording process to check for consistency in pronunciation, accentuation, and style.

USS Voices

Until about 2019, all our high quality voices were made using a technology called Unit Selection Synthesis (USS). These voices are still used in most of our SaaS solutions, such as webReader and docReader. 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).
A 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.
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. Our state-of-the-art methodologies are augmented by the linguistic expertise of our team. 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.
This is how a new ReadSpeaker TTS voice persona is born. However, the process doesn’t end there. One of ReadSpeaker’s unique characteristics is our ongoing improvement process. Through a system of high-quality feedback and a thorough Quality Assurance process by mother-tongue experts, imperfections are continuously corrected.

Neural Voices

In parallel, ReadSpeaker creates so-called neural voices, using techniques based on deep learning AI technology. This revolutionary method involves mapping linguistic properties to acoustic features using Deep Neural Networks (DNNs). An iterative learning process minimises objectively measurable differences between the predicted acoustic features and the observed acoustic features in the training set. One of the advantages of the new DNN TTS method is that the acoustic database can be much smaller than for a USS voice. 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. Also, the resulting speech is generally smoother and even more human-like. This makes developing new, smart ReadSpeaker TTS voices with even more lifelike, expressive speech and customizable intonation faster than ever.

Custom TTS Voices

If your strategy is to offer an exclusive customer experience and you want to take your brand appeal to a new level, one of the most powerful ways to differentiate yourself is by using a custom voice to represent you. A custom voice sets your brand apart and creates a powerful bond with your customers across your various communication touchpoints. If a preferred celebrity or other talent reflects your brand best and you want to be able to use their voice anytime you need it, ReadSpeaker can create a custom TTS voice powered by our leading-edge speech engine, to give your brand instant recognition in the voice user interface.