The character 一日 can be read as “いちにち” (“the whole day”), or as ついたち (“the first day of the month”). Depending on the context, the readings of some Kanji differ.
Furigana are a Japanese reading aid. They are Hiragana characters that are written next to or above a Kanji in Japanese writing to indicate its pronunciation.
Conventional Furigana software does not recognize the holistic meaning or context of a text, and is therefore sometimes unable to provide the Furigana in the way a Japanese reader would actually read the text.
However, with AI, this is now possible, which is why I programmed this software. “Smart-Furi” analyzes the text for context, tone, etc., to add the appropriate readings as Furigana to the text – so that one does not learn the readings of the characters incorrectly, but as if a Japanese person were reading the text aloud.
Interface for UNESCOs Lists of "Intangible Cultural Heritage"
The UNESCO project “Intangible Cultural Heritage” (ICH) offers an impressive collection of intangible cultural heritage as well as a register of best protection measures. These can be found on the UNESCO website in English, French, and Spanish, beautifully describing the individual cultural peculiarities of the nations of the world.
As a friend of online ethnology, I have set up a new interface in the form of an interactive world map (JavaScript, OpenStreetMap & GeoJSON). By clicking on a country, you gain insight into the culture of that country as registered by UNESCO (UNESCO Open Access Database). Using the ChatGPT API and Python, I translated the entire database into the 10 most spoken languages in the world. Additionally, I improved/enlarged all images from the database with Topaz AI.
By clicking on the cube, a random entry is displayed. Discover the world!
Note: Not suitable for mobile view
Sources:
UNESCO Open Access Database: Metadata, descriptions, and images from the UNESCO ICH database were used for this project.
OpenStreetMap: The map representation is based on tiles from OpenStreetMap.
GeoJSON World Map: The vector data for the country outlines comes from the open-source GeoJSON project.
IPAPI (ipapi.co): Automatic location determination is done via the API service ipapi.co.
Topaz AI: The images from the UNESCO database were upscaled using Topaz AI.
ChatGPT (OpenAI): The translations of the UNESCO data into 10 languages were created using ChatGPT.
This project is an experimental, non-commercial portfolio project and is for demonstration purposes only. All content (images, texts, titles) is the property of UNESCO. The translations were created using AI (ChatGPT). The map tiles come from OpenStreetMap. There is no connection to UNESCO, OpenStreetMap, or other organizations. The complete UNESCO metadata is available for download in English.
AI-Translate
WordPress plugin to automatically translate pages, posts, and custom type posts as well as their titles and custom fields. The translations are stored in the metadata of the posts. Depending on the selected language, the frontend displays the language under the same URL / post ID. In the Gutenberg editor, there is a small dropdown menu that allows you to switch between languages to make individual changes, and in the backend, unlike with Polylang, there is no confusing duplication of content. The translation is done via ChatGPT, which allows for context-specific translation – by specifying what the tone should be, e.g., polite or informal, and what the focus should be, such as project presentation, marketing, etc., better translations can be obtained.
The code for selecting and processing content is available in a git repository.
Jōyō-Kanji
The 2136 Kanji that are learned in elementary and middle school in Japan, which enable one to read most Japanese texts, along with their translations in German.
The meaning of a word often varies depending on the context. Many terms only arise when multiple Kanji are combined – that’s why the term “you” is not found here, for example. It is composed of 貴 (valuable, noble, precious) and 方 (person).
The question of how to comprehensively categorize a language has proven to be very interesting. The categorization by “school year” is a time-honored Japanese method – but the desire for finer granularity was present to make learning easier.
The Kanji list as a JSON file, the Python codes to create them, as well as the chosen categories can be found below in the git repository.
Painted World - Engine for 3D Figures on Pre-rendered Background Images
Inspired by games where 3D characters walk around in 2D images (games with “Pre-rendered background”) such as Final Fantasy VIII, an engine based on JavaScript to develop such games for the web browser.
Cubemap Creator
Python script to generate skybox image maps in rectangular format from equirectangular images, as well as a setup for Blender to render equirectangular image maps.
With the Blender setup, an equirectangular HDRI can be rendered from a 3D environment, like the following:
.. to then convert this into a cubemap with the Python script…
… so that this can be used in game engines like Verge3D or Goldsource.
ba.pbr.vmt.qc.mdl.exe
This is a tool designed to make it easier to implement 3D models into Valve Software’s Source game engine, better to say, KAFF Softwares port of that engine with support for physically based rendering. It offers a pipeline to compile .smd 3D mesh data and .png or .tga pixel textures to .mdl with PBR materials by simply dragging and dropping a 3D model and its set of textures onto the program for it to compile it for the Source Engine. Here’s what it does: – Create a PBR texture map from a metallic, a roughness, and an ambient occlusion map – Wrap VTFCmd.exe to generate Source engine compatible .vtf texture files from images and a .vmt material descriptor file – Generate model and texture mapping descriptor .qc file, necessary for compilation of 3D model with textures – Wrap studiomdl.exe to compile Source engine compatible binary .mdl and .phy files from .smd and .qc files among others – the file formats which are expected by the engine
Drag & drop texture images on the tool to generate specific PBR-materials that can be used in the production of the game Boreal Alyph. The first three added textures will be merged into a single texture map, one texture per color channel (metallic, roughness, ambient occlusion). For each of these, the tool offers the option for color inversion before merging them. The tool then asks for an albedo-, normal- and height-texture map, converts everything to .vtf and writes a corresponding .vmt with the use of vtfcmd.exe. As last step, the tool asks for .smd 3D model files. It then generates a .qc corresponding to the models and textures and then compiles the model .mdl and .phy files (among others) by controlling studiomdl.exe.
Example model used:
A mesh of a wooden pallet with textures for real time physically based rendering and a collision hull mesh. Blender can export mesh data in .smd format. So this is what we got as input:
And this is what the tool makes out of it, which is (Boreal Alyph) Source Engine compatible:
Simple Ontology
Define truth! Create your own node-network graphs, also known as ontologies.
Tool for creating ontological network topologies, written in Java. Has the functionality to save and load and export images. Smallest alternative to Protégé, ONTOLIS, or OntoStudio.
Hydromatrix Controller
100 virtual fountains (Blender particle systems) in the middle of a virtual water basin are controlled in height by a depth map (black/white video). Each fountain is illuminated by a virtual RGB LED (Blender spotlights), which is controlled in color and brightness by a color map (colored video).
Blender is controlled as a server by a client program written in Java to manage 3D animation via video.
There were difficulties in running a TCP server in Blender Python, which controls parameters and viewport of Blender, in a separate thread from Blender’s Python runtime stably – the server quickly became “overloaded”. The experiment was thus successful in that it showed the limits of what I could do – reprogramming Blender’s threading was not possible for this experiment.
Amazon Keyword Wizard
This tool allows for easy creation of Amazon product texts and management of relevant keywords:
Import/Export JSON: Upload or save keyword list in JSON format to continue working later.
Writing texts: Create product titles, descriptions, and bullet points while the tool automatically checks for the inclusion of specific keywords.
Used vs. Unused Keywords: In the left area, you can always see which keywords have already been incorporated into the texts and which are still missing.
Why Keywords? Extensive keyword coverage can increase your visibility on Amazon and attract more potential customers. Different formulations with various descriptive words for the product generate more traffic.
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