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http://dx.doi.org/10.1186/s12967-023-03975-1 | DOI Listing |
Int J Lang Commun Disord
January 2025
Division of Communication Sciences and Disorders, University of Cape Town, Rondebosch, South Africa.
Background: There is a global need for synthetic speech development in multiple languages and dialects, as many children who cannot communicate using their natural voice struggle to find synthetic voices on high-technology devices that match their age, social and linguistic background.
Aims: To document multiple stakeholders' perspectives surrounding the quality, acceptability and utility of newly created synthetic speech in three under-resourced South African languages, namely South African English, Afrikaans and isiXhosa.
Methods & Procedures: A mixed methods research design was selected.
Aging Ment Health
January 2025
Department of Psychology, University of Edinburgh, Edinburgh, UK.
Objectives: Ageism occurs across the world, with negative consequences for individuals and societies. In 2016, WHO received a mandate from its Member States to lead the global campaign to combat ageism. To monitor, evaluate, and build evidence for reducing ageism, the availability of a brief, reliable and valid set of indicators of ageism experiences that can be used globally is essential.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China.
Bird species detection is critical for applications such as the analysis of bird population dynamics and species diversity. However, this task remains challenging due to local structural similarities and class imbalances among bird species. Currently, most deep learning algorithms focus on designing local feature extraction modules while ignoring the importance of global information.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Institute of Computer and Communication Engineering, Department of Electrical Engineering, National Cheng Kung University, Tainan 701, Taiwan.
Precision depth estimation plays a key role in many applications, including 3D scene reconstruction, virtual reality, autonomous driving and human-computer interaction. Through recent advancements in deep learning technologies, monocular depth estimation, with its simplicity, has surpassed the traditional stereo camera systems, bringing new possibilities in 3D sensing. In this paper, by using a single camera, we propose an end-to-end supervised monocular depth estimation autoencoder, which contains an encoder with a structure with a mixed convolution neural network and vision transformers and an effective adaptive fusion decoder to obtain high-precision depth maps.
View Article and Find Full Text PDFCancers (Basel)
January 2025
Hybrid Technology Hub, Centre of Excellence, Institute of Basic Medical Sciences, University of Oslo, 0372 Oslo, Norway.
: Tumor organoid and tumor-on-chip (ToC) platforms replicate aspects of the anatomical and physiological states of tumors. They, therefore, serve as models for investigating tumor microenvironments, metastasis, and immune interactions, especially for precision drug testing. To map the changing research diversity and focus in this field, we performed a quality-controlled text analysis of categorized academic publications and clinical studies.
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