Thumbnail
Access Restriction
Open

Author Stemmer, Georg ♦ Niemann, Heinrich
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Application Field ♦ Baseline System ♦ German Speech Recognition System ♦ Training Data ♦ Non-native Pronunciation ♦ Recognition Quality ♦ Acoustic Modeling ♦ Word Error Rate ♦ Several Method ♦ Foreign Word ♦ Phoneme Model ♦ Paper Deal ♦ Robust Acoustic Model ♦ Foreign Sound ♦ German Speech Recognizer ♦ Main Problem ♦ Entropy-based Distance Measure ♦ Acoustic Model ♦ Overall Performance ♦ German Speaker ♦ Proper Name ♦ Similar Way ♦ Spoken Dialogue System
Description The paper deals with the development of acoustic models of foreign words for a German speech recognizer. The recognition quality of foreign words is crucial for the overall performance of a system in application fields like spoken dialogue systems, when foreign words occur as proper names. One of the main problems in the modeling of foreign words is the limitation of training data, which must contain samples of the non-native pronunciation of the foreign sounds. In order to obtain robust acoustic models, which are still precise enough, we compare several methods to map or to merge the models of phonemes, which are pronounced in a similar way by German speakers. We utilize an entropy-based distance measure between sets of phoneme models. The best approach yields a reduction of 16.5 % word error rate, when compared to a baseline system.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2001-01-01
Publisher Institution Proceedings of the 7th European Conference on Speech Communication and Technology (Eurospeech-2001