Investigation of silicon auditory models and generalization of linear discriminant analysis for improved speech recognition
Speaker normalization using efficient frequency warping procedures
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
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This paper presents recent advances in Automatic Speech Recognition for the Czech Language. Improvements were achieved both in acoustic and language modeling. We mainly aim on the acoustic part of the issue. The results are presented in two contexts, the lecture recognition and SpeeCon+Temic test set. The paper shows the impact of using advanced modeling techniques such as HLDA, VTLN and CMLLR. On the lecture test set, we show that training acoustic models using word networks together with the pronunciation dictionary gives about 4---5% absolute performance improvement as opposed to using direct phonetic transcriptions. An effect of incorporating the "schwa" phoneme in the training phase shows a slight improvement.