Abstract : The growing demand for robust speech processing applications able to operate in adverse scenarios calls for new evaluation protocols and datasets beyond artificial laboratory conditions. The characteristics of real data for a given scenario are rarely discussed in the literature. As a result, methods are often tested based on the author expertise and not always in scenarios with actual practical value. This paper aims to open this discussion by identifying some of the main problems with data simulation or collection procedures used so far and summarizing the important characteristics of real scenarios to be taken into account, including the properties of reverberation, noise and Lombard effect. At last, we provide some preliminary guidelines towards designing experimental setup and speech recognition results for proposal validation.
https://hal.inria.fr/hal-01377638
Contributeur : Emmanuel Vincent
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Soumis le : vendredi 7 octobre 2016 - 12:03:48
Dernière modification le : mardi 18 décembre 2018 - 16:38:02
Document(s) archivé(s) le : vendredi 3 février 2017 - 18:44:07
Dayana Ribas, Emmanuel Vincent, José Calvo. A study of speech distortion conditions in real scenarios for speech processing applications. 2016 IEEE Workshop on Spoken Language Technology, Dec 2016, San Diego, United States. 2016. 〈hal-01377638〉
