Lessac Technology, Inc.

Lessac Technologies, Inc.

Nancy Krebs

Gary A Marple

H Donald Wilson

Anthony H Handal

Edwin Addison

Mary Louise B Wilson, Legal Representative

Diane Gaary

Sue Ann Park

Barry Kur

A method of, and system for, acoustically coding text for use in the synthesis of speech from the text. The method includes marking the text to be spoken with one or more graphic symbols to indicate to a speaker a desired prosody to impart to the spoken text. The markups can include grapheme-phoneme pairs each wherein a visible prosodic-indicating grapheme is employed with written text and a corresponding digital phoneme is functional in the digital domain. The invention is useful in the generation of appealing, humanized machine speech for a wide range of applications, including voice mail systems, electronically enabled appliances, automobiles, computers, robotic assistants, games and the like, in spoken books and magazines, drama and other entertainment.

Prosodic speech text codes and their use in computerized speech systems

A preferred embodiment of the method for converting text to speech using a computing device having a memory is disclosed. The inventive method comprises examining a text to be spoken to an audience for a specific communications purpose, followed by marking-up the text according to a phonetic markup systems such as the Lessac System pronunciation rules notations. A set of rules to control a speech to text generator based on speech principles, such as Lessac principles. Such rules are of the tide normally implemented on prior art text-to-speech engines, and control the operation of the software and the characteristics of the speech generated by a computer using the software. A computer is used to speak the marked-up text expressively. The step of using a computer to speak the marked-up text expressively is repeated using alternative pronunciations of the selected style of expression where each of the tonal, structural, and consonant energies, have a different balance in the speech, are also spoken to a trained speech practitioners that listened to the spoken speech generated by the computer. The spoken speech generated by the computer is then evaluated for consistency with style criteria and/or expressiveness. And audience is then assembled and the spoken speech generated by the computer is played back to the audience. Audience comprehension of spoken speech generated by the computer is evaluated and correlated to a particular implemented rule or rules, and those rules which resulted relatively high audience comprehension are selected.

Text to speech

A preferred embodiment of the method for converting text to speech using a computing device having a memory is disclosed. Text, being made up of a plurality of words, is received into the memory of the computing device. A plurality of phonemes are derived from the text. Each of the phonemes is associated with a prosody record based on a database of prosody records associated with a plurality of words. A first set of the artificial intelligence rules is applied to determine context information associated with the text. The context influenced prosody changes for each of the phonemes is determined. Then a second set of rules, based on Lessac theory to determine Lessac derived prosody changes for each of the phonemes is applied. The prosody record for each of the phonemes is amended in response to the context influenced prosody changes and the Lessac derived prosody changes. Then a reading from the memory sound information associated with the phonemes is performed. The sound information is amended, based on the prosody record as amended in response to the context influenced prosody changes and the Lessac derived prosody changes to generate amended sound information for each of the phonemes. Then the sound information is outputted to generate a speech signal.

Expressive parsing in computerized conversion of text to speech

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Severn, MD, United States of America

Nancy Krebs