Sixth International Conference on Spoken Language Processing
October 16-20, 2000
Combination of Acoustic Models in Continuous Speech Recognition Hybrid Systems
Hugo Meinedo, Joao P. Neto
INESC - IST, Lisboa, Portugal
The combination of multiple sources of information has
been an attractive approach in different areas. That is the
case of speech recognition area where several combination
methods have been presented. Our hybrid MLP/HMM systems
use acoustic models based on different set of features
and different MLP classifier structures. In this work we developed
a method combining phoneme probabilities generated
by the different acoustic models trained on distinct
feature extraction processes. Two different algorithms were
implemented for combining the acoustic models probabilities.
The first covers the combination in the probability
domain and the second one in the log-probability domain.
We made combinations of two and three alternative baseline
systems where was possible to obtain relative improvements
on word error rate larger than 20% for a large vocabulary
speaker independent continuous speech recognition
Meinedo, Hugo / Neto, Joao P. (2000):
"Combination of acoustic models in continuous speech recognition hybrid systems",
In ICSLP-2000, vol.2, 931-934.