Modeling Improved Prosody Generation from High-Level Linguistically Annotated Corpora

Modeling Improved Prosody Generation from High-Level Linguistically Annotated Corpora

Synthetic speech usually suffers from bad F0 contour surface. The prediction of the underlying pitch targets robustly relies on the quality of the predicted prosodic structures, i.e. the corresponding sequences of tones and breaks. In the present work, we have utilized a linguistically enriched annotated corpus to build data-driven models for predicting prosodic structures with increased accura...

Linguistically Annotated Corpora: Quality Assurance, Reusability and Sustainability

EULIA: a graphical web interface for creating, browsing and editing linguistically annotated corpora

In this paper we present EULIA, a tool which has been designed for dealing with the linguistic annotated corpora generated by a set of different linguistic processing tools. The objective of EULIA is to provide a flexible and extensible environment for creating, consulting, visualizing, and modifying documents generated by existing linguistic tools. The documents used as input and output of the...

Linguistically Annotated Learner Corpora: Aspects of a Layered Linguistic Encoding and Standardized Representation

Linguistically annotated corpora that are stored in standardized digital form can be a valuable source of empirical insight. They can help verify linguistic generalizations and support the formulation of new hypotheses. The linguistic annotation of such corpora often is crucial for their effective exploration from a linguistic perspective. The annotation essentially serves as an index to the li...

Training Dependency Parsers from Partially Annotated Corpora

We introduce a maximum spanning tree (MST) dependency parser that can be trained from partially annotated corpora, allowing for effective use of available linguistic resources and reduction of the costs of preparing new training data. This is especially important for domain adaptation in a real-world situation. We use a pointwise approach where each edge in the dependency tree for a sentence is...