Abstract
Embedded devices incorporate everyday new applications in different domains due to their increasing computational power.Many of these applications have a voice interface that uses Automatic Speech Recognition (ASR). When the complexity of the language model is high, it is common to use an external server to perform the recognition at the expense of certain limitations (network availability, latency, etc.). This paper focuses on a new proposal to improve the efficiency of the usage of the language model in a recognizer for multiple domains. The idea is based on the selection of a proper language model for each domain within the ASR system.
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Santos-Pérez, M., González-Parada, E., Cano-García, J.M. (2012). Topic-Dependent Language Model Switching for Embedded Automatic Speech Recognition. In: Novais, P., Hallenborg, K., Tapia, D., Rodríguez, J. (eds) Ambient Intelligence - Software and Applications. Advances in Intelligent and Soft Computing, vol 153. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28783-1_30
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DOI: https://doi.org/10.1007/978-3-642-28783-1_30
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