Using an HPSG grammar for the generation of prosody

Abstract

In this paper, we report on an experiment showing how the introduction of prosodic information from detailed syntactic structures into synthetic speech leads to better disambiguation of structurally ambiguous sentences. Using modifier attachment (MA) ambiguities and subject/object fronting (OF) in German as test cases, we show that prosody which is automatically generated from deep syntactic information provided by an HPSG generator can lead to considerable disambiguation effects, and can even override a strong semantics-driven bias. The architecture used in the experiment, consisting of the LKB generator running a large-scale grammar for German, a syntax-prosody interface module, and the speech synthesis system MARY is shown to be a valuable platform for testing hypotheses in intonation studies.