TY  - JOUR
AU  - Mišković, Dragiša
AU  - Gnjatović, Milan
AU  - Štrbac, Perica
AU  - Trenkić, Branimir
AU  - Jakovljević, Nikša
AU  - Delić, Vlado
PY  - 2017
UR  - http://jakov.kpu.edu.rs/handle/123456789/1520
AB  - 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.
PB  - London : SAGE Publications
T2  - International Journal of Advanced Robotic Systems
T1  - Hybrid methodological approach to context-dependent speech recognition
VL  - 14
IS  - 1
DO  - 10.1177/1729881416687131
ER  - 

@article{
author = "Mišković, Dragiša and Gnjatović, Milan and Štrbac, Perica and Trenkić, Branimir and Jakovljević, Nikša and Delić, Vlado",
year = "2017",
abstract = "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.",
publisher = "London : SAGE Publications",
journal = "International Journal of Advanced Robotic Systems",
title = "Hybrid methodological approach to context-dependent speech recognition",
volume = "14",
number = "1",
doi = "10.1177/1729881416687131"
}

Mišković, D., Gnjatović, M., Štrbac, P., Trenkić, B., Jakovljević, N.,& Delić, V.. (2017). Hybrid methodological approach to context-dependent speech recognition. in International Journal of Advanced Robotic Systems
London : SAGE Publications., 14(1).
https://doi.org/10.1177/1729881416687131

Mišković D, Gnjatović M, Štrbac P, Trenkić B, Jakovljević N, Delić V. Hybrid methodological approach to context-dependent speech recognition. in International Journal of Advanced Robotic Systems. 2017;14(1).
doi:10.1177/1729881416687131 .

Mišković, Dragiša, Gnjatović, Milan, Štrbac, Perica, Trenkić, Branimir, Jakovljević, Nikša, Delić, Vlado, "Hybrid methodological approach to context-dependent speech recognition" in International Journal of Advanced Robotic Systems, 14, no. 1 (2017),
https://doi.org/10.1177/1729881416687131 . .