Hybrid methodological approach to context-dependent speech recognition
| Autor: | Dragiša Mišković, Milan Gnjatović, Perica Štrbac, Branimir Trenkić, Nikša Jakovljević, Vlado Delić |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | International Journal of Advanced Robotic Systems, Vol 14 (2017) |
| Druh dokumentu: | article |
| ISSN: | 1729-8814 17298814 |
| DOI: | 10.1177/1729881416687131 |
| Popis: | Although the importance of contextual information in speech recognition has been acknowledged for a long time now, it has remained clearly underutilized even in state-of-the-art speech recognition systems. This article introduces a novel, methodologically hybrid approach to the research question of context-dependent speech recognition in human–machine interaction. To the extent that it is hybrid, the approach integrates aspects of both statistical and representational paradigms. We extend the standard statistical pattern-matching approach with a cognitively inspired and analytically tractable model with explanatory power. This methodological extension allows for accounting for contextual information which is otherwise unavailable in speech recognition systems, and using it to improve post-processing of recognition hypotheses. The article introduces an algorithm for evaluation of recognition hypotheses, illustrates it for concrete interaction domains, and discusses its implementation within two prototype conversational agents. |
| Databáze: | Directory of Open Access Journals |
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