Abstract
AbstractThe paper analyzes both acoustic and linguistic features with different Chinese prosodic boundaries. Then a rule-learning approach was used to do the prosodic boundary labelling. In the paper the prosodic boundaries are classified into four levels, full intonational boundary with strong intonational marking with/without lengthening or change in speech tempo, prosodic phrase boundary with rather weak intonational marking, prosodic word boundary and phone foot boundary. Candidate acoustic and linguistic features related to prosodic boundary were extracted from the corpus to establish an example database. Based on this, a series of comparative experiments is conducted to collect the most effective features from the candidates. Results show that the selected candidates characterize the boundary features efficiently. Final experiments show that rule-learning approach introduced in the paper can achieve better prediction accuracy than the rule and RNN based methods and yet retain the advantage of the simplicity and understandability.KeywordsAcoustic ParameterLinguistic FeatureLinguistic InformationProsodic FeaturePhrase BoundaryThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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