Datenbasierte und linguistisch interpretierbare Intonationsmodellierung

In this thesis a data-driven and linguistically interpretable
intonation model for the automatic analysis and synthesis of
fundamental frequency (F0) contours was developed. The model can be
characterised as parametric, contour-based, and superpositional.
Its intonation representation consists of a superposition of global
and local contour classes and can be derived in a purely
data-driven manner, which guarantees consistency and easy
adaptability to new data. The model's linguistic interpretability
was examined by automatic linguistic corpus analyses resulting in
hypotheses about possible relations between contours and linguistic
concepts. These hypotheses were subsequently tested by perception
experiments. By these means a systematic linguistic anchoring of
the model was achieved in form of a decision tree to predict the
linguistically appropriate contour class. The adequacy of its
predictions was assured by a further perception test. Due to its
simultaneous signal proximity and linguistic anchoring, the model
covers the entire chain from text to signal and therefore can be
used for intonation analysis and generation on a linguistic as well
as on a phonetic-acoustic level. It is qualified for employment in
speech technology applications as well as in phonetic fundamental
research to automatically analyse raw speech data.