The RWTH Large Vocabulary Speech Recognition System for Spontaneous Speech

This paper presents details of the RWTH large vocabulary continuous speech recognition system used in the VERBMOBIL spontaneous speech translation system. In particular, we report on methods for accelerating the search and algorithms for fast vocal tract normalization (VTN). We focus both on the improvements in word error rate and how to speed up the recognizer with only minimal loss in recognition accuracy. Implementation details and experimental results are given for the VERBMOBIL German development corpus dev99. The 24.6% word error rate of the baseline system is reduced to 22.8% using VTN. Decreasing the real-time factor by a factor of 5 resulted in only a small degradation in recognition performance of 2% relative on average. Furthermore, we study incremental methods for reducing the response time of the online speech recognizer and an efficient method to reduce the density of word graphs.

• Type: Conference
• Year: 2000
• Where: KONVENS
• Authors: Stephan Kanthak, Sirko Molau, Achim Sixtus, Ralf Schlüter, Hermann Ney
• Keywords: Continuous Speech Recognition, KONVENS 2000, Natural Language Processing, VERBMOBIL Spontaneous Speech, Word Error Rate