Information content, weighting and distribution in continuous speech prosody - A cross-genre comparison

Abstract

This study explores the composition of information content in continuous speech using data of a diversity of speech genres. Our approach is to measure information weighting, distribution and correlative expressiveness through perceived prosodic prominences in continuous speech from data of 4 different styles. This alternative perspective differs from reported studies on emotion related prosodic expressions and is based mainly on the assumption that patterned prominences are also positively correlated with the allocation and weighted loading of information, but only by higher level of discourse units. Four speech genres, i.e., 2 styles of read vs. 2 of spontaneous speech annotated with perceived prominences at 4 relative degrees are compared. Information allocation and weighting are calculated using both frequency count of prominence patterns and designation of weighting scores by prominence levels. The most revealing results are found in data of spontaneous conversation, which feature in more varieties of emphasis patterns as results of constant reduction. Far more significantly, conversation data also showcase that while their paragraph-level prosodic units carry the least amount of information content, the discourse-level prosodic units exhibit the highest score of information weighting. In other words, one major but less known distinctive feature of conversation speech is its largest amount of information content, which only surfaces when examined by the highest level of discourse-prosodic unit. We believe the results have furthered our understanding of prosody expressions in continuous speech in general and spontaneous conversation in particular; and could readily be utilized in many speech technology related implementations.