Robustness Optimization of a Speech Interface for Child-Directed Embedded Language Tutoring

摘要

This contribution describes the robustness evaluation and optimization steps for a speech interface which is suitable for embedded language tutoring with special focus on children's speech. The baseline algorithms are derived from the pronunciation tutoring system AzAR directed to adult learners of German. The first prototype LiSA (2008) - directed to young children starting at 3 years - is currently evaluated and optimized, mainly addressing following issues: (a) the challenge of ASR-based pronunciation assessment for children's speech, (b) the handling of noise and reverberation in an embedded application scenario, and (c) the extraction of additional information such as age or gender. The article summarizes evaluation results of the speech recognizer in laboratory and real-world room environment.