| Issue |
MATEC Web Conf.
Volume 309, 2020
2019 International Conference on Computer Science Communication and Network Security (CSCNS2019)
|
|
|---|---|---|
| Article Number | 05007 | |
| Number of page(s) | 7 | |
| Section | Modelling and Simulation | |
| DOI | https://doi.org/10.1051/matecconf/202030905007 | |
| Published online | 04 March 2020 | |
Acoustic model topology optimization for large vocabulary speech recognition
1 School of Computer Science and Engineering, Hohhot College for Nationalities, Hohhot, China
2 Library of College, Hohhot College for Nationalities, Hohhot, China
* Corresponding author: xirimo_bao@sina.com
Acoustic model topology selection work in constructing large vocabulary speech recognition systems is being done empirically or heuristically. In this paper, we propose two improved algorithms, which are based on Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) respectively, on the basis of our previously proposed algorithms to select and optimize model topologies for small or medium vocabulary speech recognition systems. Our improved algorithms attain the goal of optimizing acoustic model topologies for large vocabulary speech recognition systems mainly through modifying the encoding schemes of our previously proposed algorithms. Experiments on the dialogue corpus of Inner Mongolia University show that, compared with the conventional acoustic model topology selection method, our newly proposed algorithms are able to bring much higher recognition performance for large vocabulary speech recognition systems by optimizing their acoustic model topologies.
Key words: Acoustic model / Topology optimization / Genetic algorithm / Particle swarm optimization / Speech recognition
© The Authors, published by EDP Sciences, 2020
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