Title :
Java tools for teaching speech recognition
Author_Institution :
Fachhochschule Giessen-Friedberg, Univ. of Appl. Sci., Friedberg, Germany
Abstract :
In this paper, we present our concept for a sequence of experiments with speech recognizers used in teaching speech recognition techniques. The experiments are performed with a combination of own tools and the hidden Markov toolkit (HTK). The first experiment demonstrates speaker dependent recognition based on the dynamic time warp algorithm. In the course of this experiment all utterances from the students are recorded and used to build up a data base. Both the recognizer and the tool used for viewing and editing the speech data are written in Java making them platform independent and easy to extend. The recorded speech data is then utilized to train and test a speaker independent recognizer.
Keywords :
Java; educational aids; hidden Markov models; speech recognition; HTK; Java tools; dynamic time warp algorithm; hidden Markov toolkit; speaker dependent recognition; speaker independent recognizer; speech data editor; speech data viewer; speech recognition teaching; student recorded utterance data base; Education; Feature extraction; Heuristic algorithms; Hidden Markov models; Java; Linear predictive coding; Signal analysis; Speech analysis; Speech recognition; Testing;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
Print_ISBN :
0-7803-8874-7
DOI :
10.1109/ICASSP.2005.1416360