This paper addresses issues that are specific to the implementation of automatic speech recognition (ASR) applications and services in client-server scenarios. It is assumed in all of these scenarios that functionality in a human-machine dialog system is distributed between mobile client devices and network based multi-user media and application servers. It is argued that, while there has already been a great deal of research addressing issues relating to the communications channels associated with these scenarios, there are many additional problems that have received relatively little attention. These include issues of how environmental and speaker robustness algorithms are implemented in mobile domains and how multiple ASR channels can be implemented more efficiently in multi-user deployments. Preliminary results are summarized showing the effect of user specific unsupervised adaptation and normalization algorithms on ASR performance in mobile domains. Results are also presented demonstrating the efficiencies that are obtainable from using intelligent algorithms for assigning ASR decoders to computation servers in multi-user deployments.
Cite as: Rose, R., Kim, H.K. (2004) Robust speech recognition in client-server scenarios. Proc. Interspeech 2004, 2321-2324, doi: 10.21437/Interspeech.2004-686
@inproceedings{rose04_interspeech,
author={Richard Rose and Hong Kook Kim},
title={{Robust speech recognition in client-server scenarios}},
year=2004,
booktitle={Proc. Interspeech 2004},
pages={2321--2324},
doi={10.21437/Interspeech.2004-686}
}