Punctuation-generation-inspired linguistic features for Mandarin prosody generation

Abstract

This paper proposes two novel linguistic features extracted from text input for prosody generation in a Mandarin text-to-speech system. The first feature is the punctuation confidence (PC), which measures the likelihood that a major punctuation mark (MPM) can be inserted at a word boundary. The second feature is the quotation confidence (QC), which measures the likelihood that a word string is quoted as a meaningful or emphasized unit. The proposed PC and QC features are influenced by the properties of automatic Chinese punctuation generation and linguistic characteristic of the Chinese punctuation system. Because MPMs are highly correlated with prosodicacoustic features and quoted word strings serve crucial roles in human language understanding, the two features could potentially provide useful information for prosody generation. This idea was realized by employing conditional random-field-based models for predicting MPMs, quoted word string locations, and their associated confidences-that is, PC and QC-for each word boundary. The predicted punctuations and their confidences were then combined with traditional linguistic features to predict prosodic-acoustic features for performing speech synthesis using multilayer perceptrons. Both objective and subjective tests demonstrated that the prosody generated with the proposed linguistic features was superior to that generated without the proposed features. Therefore, the proposed PC and QC are identified as promising features for Mandarin prosody generation.

Superposition of Functional Contours Based Prosodic Feature Extraction for Speech Processing

“…Breen [20] implemented event-based approaches for the representation of implicit prosodic details and compared their performances to those of [x]. Prosody was generated by Chiange [21] precisely for the mandarin language TTS system. The researcher used two linguistic features of the language to accomplish this.…”