Abstract: Embodiments of the present systems and methods may provide techniques for synthesizing speech in any voice in any language in any accent. For example, in an embodiment, a text-to-speech conversion system may comprise a text converter adapted to convert input text to at least one phoneme selected from a plurality of phonemes stored in memory, a machine-learning model storing voice patterns for a plurality of individuals and adapted to receive the at least one phoneme and an identity of a speaker and to generate acoustic features for each phoneme, and a decoder adapted to receive the generated acoustic features and to generate a speech signal simulating a voice of the identified speaker in a language.

Abstract: Embodiments of the present systems and methods may provide techniques for synthesizing speech in any voice in any language in any accent. For example, in an embodiment, a text-to-speech conversion system may comprise a text converter adapted to convert input text to at least one phoneme selected from a plurality of phonemes stored in memory, a machine-learning model storing voice patterns for a plurality of individuals and adapted to receive the at least one phoneme and an identity of a speaker and to generate acoustic features for each phoneme, and a decoder adapted to receive the generated acoustic features and to generate a speech signal simulating a voice of the identified speaker in a language.

Abstract: Embodiments of the present systems and methods may provide techniques for synthesizing speech in any voice in any language in any accent. For example, in an embodiment, a text-to-speech conversion system may comprise a text converter adapted to convert input text to at least one phoneme selected from a plurality of phonemes stored in memory, a machine-learning model storing voice patterns for a plurality of individuals and adapted to receive the at least one phoneme and an identity of a speaker and to generate acoustic features for each phoneme, and a decoder adapted to receive the generated acoustic features and to generate a speech signal simulating a voice of the identified speaker in a language.

Abstract: Technology for providing a translated content item containing text is disclosed. In one example, a method is used for providing a translated content item and a plurality of actions. The method can include generating a base knowledge level of terminology and generating a translated content item having a plurality of translated text, wherein the plurality of translated text is generated based at least in part on the base knowledge level. The method can further include generating a query to verify an understanding of the translated content item and updating the base knowledge level of terminology based on a response to the query.

Abstract: Technology for providing a translated content item containing medical terms is disclosed. In one example, a method is used for providing a translated content item and a plurality of actionable options. The method can include generating a base user knowledge level of medical terminology for a user and generating a translated content item having a plurality of translated medical terms, wherein the plurality of translated medical terms are generated based at least in part on the base user knowledge level. The method can further include generating a question to verify user understanding of the translated content item and updating the base user knowledge level of medical terminology based on a response to the question.