Towards Realizing Sign Language-to-Speech Conversion by Combining Deep Learning and Statistical Parametric Speech Synthesis

An, Xiaochun; Yang, Hongwu; Gan, Zhenye

doi:10.1007/978-981-10-2053-7_61

Cited by 4 publications

(1 citation statement)

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“…The picture is radically different when it comes to sign recognition towards written language, with a clear trend in the use of machine learning, particularly deep learning with multiple layers [53,54] and to a large extent the use of the statistical approach. Moreover, recent proposals combine deep learning with statistical methods [55,56].…”

Section: Findings and Challengesmentioning

confidence: 99%

A Systematic Mapping of Translation-Enabling Technologies for Sign Languages

et al. 2019

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Sign languages (SL) are the first language for most deaf people. Consequently, bidirectional communication among deaf and non-deaf people has always been a challenging issue. Sign language usage has increased due to inclusion policies and general public agreement, which must then become evident in information technologies, in the many facets that comprise sign language understanding and its computational treatment. In this study, we conduct a thorough systematic mapping of translation-enabling technologies for sign languages. This mapping has considered the most recommended guidelines for systematic reviews, i.e., those pertaining software engineering, since there is a need to account for interdisciplinary areas of accessibility, human computer interaction, natural language processing, and education, all of them part of ACM (Association for Computing Machinery) computing classification system directly related to software engineering. An ongoing development of a software tool called SYMPLE (SYstematic Mapping and Parallel Loading Engine) facilitated the querying and construction of a base set of candidate studies. A great diversity of topics has been studied over the last 25 years or so, but this systematic mapping allows for comfortable visualization of predominant areas, venues, top authors, and different measures of concentration and dispersion. The systematic review clearly shows a large number of classifications and subclassifications interspersed over time. This is an area of study in which there is much interest, with a basically steady level of scientific publications over the last decade, concentrated mainly in the European continent. The publications by country, nevertheless, usually favor their local sign language.

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Section: Findings and Challengesmentioning

confidence: 99%