This guide is intended to support crisis-affected community members to hold humanitarian organizations accountable for their safe and responsible use of digital technology. This technology may be newly developed digital tools or existing tools combined in new ways. It includes
Making a regular practice of exploring innovative technological solutions to problems and gaps in humanitarian responses offers immense potential for improved and more sustainable service delivery, even as a crisis evolves into a longer-term development phase. To achieve the most
Read the 2024 Annual Report now. 2024 was a year of maturity for the organization. We are moving toward more sustainable income sources and less dependency on short-term humanitarian funding. This has meant focusing our work. It seemed that the
Voice datasets are structured collections of audio recordings paired with corresponding text transcriptions, metadata, and annotations. These datasets serve as the foundation for training and evaluating speech recognition systems, text-to-speech engines, and other voice-enabled applications. High-quality voice datasets are essential
Voice datasets are structured collections of audio recordings paired with corresponding text transcriptions, metadata, and annotations. These datasets serve as the foundation for training and evaluating speech recognition systems, text-to-speech engines, and other voice-enabled applications. High-quality voice datasets are essential
Indigenous communities in Bolivia want access to practical, actionable and timely early warning systems in a language that they can understand. They are increasingly exposed to a range of climate change-related threats that are reshaping their cultural and spiritual landscapes.
Changing direction is never very easy; in 2022 we developed a new Direction of Travel, focusing more on developing partnerships and language technology to reach our goal of enabling 4 billion conversations. This is very exciting! And it takes time
Learn how we are exploring the potential of synthetic data to improve automatic speech recognition for low-resource African languages Africa is home to over 2,300 languages, and the majority of them are unsupported by both automatic speech recognition (ASR) to
The TWB Voice Playbook is a practical guide to planning and managing voice data collection projects for low-resource languages. It is aimed at both new and experienced teams and covers the full process, from setting up the project to publishing
Below is a curated collection of open resources for text-to-speech (TTS), automatic speech recognition (ASR), and synthetic voice datasets in the Chichewa language. Text-to-Speech (TTS) Models Explore our collection of Chichewa TTS models, including XTTS and other multilingual models fine-tuned
Below is a curated collection of open resources for text-to-speech (TTS), automatic speech recognition (ASR), and synthetic voice datasets in the Hausa language. Text-to-Speech (TTS) Models Explore our collection of Hausa TTS models, including XTTS and other multilingual models fine-tuned
Below is a curated collection of open resources for text-to-speech (TTS), automatic speech recognition (ASR), and synthetic voice datasets in the Dholuo language. Text-to-Speech (TTS) Models Explore our collection of Dholuo TTS models, including XTTS and other multilingual models fine-tuned
