Automatic Detection of Phrase Boundaries and Highlighting Phrases in Text

This disclosure describes techniques to display text in a way that enhances readability through phrasal grouping. Using dependency-parsing techniques, sentences are automatically split into phrases. The display of text is adapted to phrasal groupings, e.g., using highlighting, with or without synchronized audio. For example, a text-to-speech (TTS) reader voices phrases sequentially while the phrase currently being voiced is synchronously highlighted. The grouping of text into phrases and their highlighting during audio-visual consumption by the user can improve comprehension

Publications: Automatic Detection of Prosody Phrase Boundaries For Text-to-Speech System AUTOMATIC DETECTION OF PROSODY PHRASE BOUNDARIES FOR TEXT-TO-SPEECH SYSTEM

Automatic acquisition of the prosodic phrase boundary detecting rules from the text and speech corpora has always been a difficulty for TTS systems. We collected over 5,000 sentences as the corpus, introduced a method based on the transform-based error-driven learning to get the rules for detecting prosodic phrase boundaries, and then used trees to organize the rules in the TTS system. For using the transformation-based error-driven learning, we designed a set of templates especially. Using 1,000 sentences to get rules for the TTS system can reach 92 % accuracy in close-test and 73 % accuracy in open-test.