Andreas Mengel

The MATE workbench – An annotation tool for XML coded speech corpora

Abstract This paper describes the design and implementation of the MATE workbench, a program which provides support for the annotation of speech and text. It provides facilities for flexible display and editing of such annotations, and complex querying of a resulting corpus. The workbench offers a more flexible approach than most existing annotation tools, which were often designed with a specific annotation scheme in mind. Any annotation scheme can be used with the MATE workbench, provided it is coded using XML markup (linked to the speech signal, if available, using certain conventions). The workbench uses a transformation language to define specialised editors optimised for particular annotation tasks, with suitable display formats and allowable editing operations tailored to the task. The workbench is written in Java, which means that it is platform-independent. This paper outlines the design of the workbench software and compares it with other annotation programs.

Query language for access to speech corpora

Typically, speech corpora are designed for the study of speech, its patterns, and their influences. Corpora for synthesis support the extraction and reuse of units in concatenative speech synthesis systems. Recent approaches consider speech segments of variable length, to enhance naturalness. The development of spoken language dialog systems (SLDSs) and similar applications requires dialog corpora with multiple information, such as prosodic labeling, grammatical annotations, dialog acts, etc. For constructing such multilevel corpora and, particularly, for retrieving useful information from there, three aspects are crucial: A theory for the description of the corpora, an effective markup and methods for specifying, and efficiently retrieving relevant portions of the data. MATE (EU Telematics Project LE4‐8370) proposes standards for an integrated and consistent multilevel annotation based on the existing TEI standard (Text Encoding Initiative). For the access to massively marked‐up speech data, a query lang...