Document Type : Full Research Paper

Authors

• Shahla Azizi ¹
• Farzad Towhidkhah ²
• Farshad Almasganj ³

¹ M. Sc, Bioelectric Department, Faculty of Biomedical Engineering, Amirkabir University of Technology

² Associate Professor, Bioelectric Department, Faculty of Biomedical Engineering, Amirkabir University of Technology

³ 3Associate Professor, Bioelectric Department, Faculty of Biomedical Engineering, Amirkabir University of Technology

Abstract

In present work, recognition of isolated word has been studied. The purpose of this research is to increase the performance of children’s speech recognizer using Vocal Tract Length Normalization. This recognition system has been created to design a speech therapy software. Recognition of correct and wrong pronunciation and help children to improve it using some feedbacks are the goals of this software. In test phase, some speech data that are related to correct and incorrect pronunciation of 47 words have been utilized. Four Baseline models have been Trained, one for children, one combined model (females and children) and two for Adults (by exploiting one Persian database). Children’s model was trained and tested with data that have been collected from 38 children (5 to 8 years old). These experiments were implemented in HTK toolkit. Poor performance was improved using VTLN. Improvement of adult’s model was more than children’s model.

Keywords

• Children speech recognition
• Vocal Tract Length Normalization
• Speaker adaptation
• Children speech therapy software
• Hidden Markov Models

Main Subjects

• Speech processing