According to Apple, a method and apparatus is provided for generating speech that sounds more natural. In one embodiment, word prominence and latent semantic analysis are used to generate more natural sounding speech. A method for generating speech that sounds more natural may comprise generating synthesized speech having certain word prominence characteristics and applying a semantically-driven word prominence assignment model to specify word prominence consistent with the way humans assign word prominence. A speech representative of a current sentence is generated. The determination is made whether information in the current sentence is new or previously given in accordance with a semantic relationship between the current sentence and a number of preceding sentences. A word prominence is assigned to a word in the current sentence in accordance with the information determination.

Here's Apple's summary of the invention: "A method and apparatus for generating speech that sounds more natural are described. According to one aspect of the present invention, a method for generating speech that sounds more natural comprises generating synthesized speech having certain word prominence characteristics and applying a semantically-driven word prominence assignment model to assign word prominence characteristics consistent with the way humans assign word prominence. In one embodiment, the word prominence assignment model employs latent semantic analysis.

"According to one aspect of the invention, as each new sentence in a text to speech generator is generated, a word prominence specification system develops a word prominence assignment model by determining semantic anchors representing the preceding sentences and semantic anchors representing the general discourse domain. The word prominence specification system classifies each word in the current sentence against the semantic anchors, and obtains an appropriate score to characterize the "novelty" of the words in the current and preceding sentences in view of the general discourse domain, i.e., to characterize which information in the current sentence is new.

"According to one aspect of the present invention, a machine-accessible medium has stored thereon a plurality of instructions that, when executed by a processor, cause the processor to generate synthesized speech having certain word prominence characteristics and apply a semantically-driven word prominence assignment model to assign word prominence characteristics consistent with the way humans assign word prominence. The instructions, when executed, may cause the processor to create synthesized speech by developing a word prominence assignment model including semantic anchors associated with the current and preceding sentences and the general discourse domain. The instructions may further cause the processor to determine whether a word in the current sentence represents new information by applying the model to a current sentence to classify each word against the semantic anchors.

"According to one aspect of the present invention, an apparatus to generate speech that sounds more natural includes a speech synthesizer to generate synthesized speech and a semantically-driven word prominence assignment model to assign word prominence characteristics consistent with the way humans assign work prominence. The word prominence assignment model may include semantic anchors associated with the current and preceding sentences and the general discourse domain. The model may then be applied to a current sentence to classify each word of the sentence against the semantic anchors."

The inventors are Jerome R. Bellegarda and Kim E. A. Silverman. The graphic below shows one embodiment of a speech synthesis system having a word prominence specification system.