Home

サイトマップ

現在、全てのページは英語のみで構成されています。ご不便をおかけします。母国語は日本語のため、メールやTwitterのリプライについては、日本語対応が可能です。

連絡先(メール、Twitter、GitHubなど): Contact

Sitemap

Home This page you are seeing now.
Articles Miscellaneous articles.
Apps Groups of self-made web apps.
Profile Information about me.
Contact Contact information such as e-mail, Twitter, GitHub, etc.

Recent Activities

  1. yBrainfuck

    I created a new programming language yBrainfuck. This is based on Brainfuck but a bit more human-writable. See the GitHub repository for the specifications or you can try it right now using our web interpreter.

    Here is a Hello World program:

  2. FizzBuzz with 50 Languages

    I've implemented the FizzBuzz game with more than 60 programming languages.

  3. Realtime Voice Recognition

    Are you interested in realtime voice recognition? Try my webapp Realtime Voice Recognition. I also supply Text to Speech, which does the reverse operation.

  4. A Patch for Netrw

    Recently I found a disastrous bug in netrw, which is an essential plugin shipped with vim by default, and wrote a patch for it. The patch has already been adopted.

  5. ympd++

    I started developing ympd++ music player, which is a fork of the original ympd, since it lacks in some fundamental functionalities and is no longer maintained.

    Dark mode, seek buttons and a cover art display are newly implemented, for example.

  6. Command Line Stack for Bash

    A script which memorizes/restores a command-line just with Ctrl + b. Simple, but quite useful.

  7. YouTube Chat Bot

    A YouTube chat bot which periodically collects chat messages from a live stream into a pool, chooses randomly an element from the pool and finally re-posts it to another or the same live stream. In the demo below, each chat is appended with a random emoji and re-posted to another live stream (the left window). This project was created for research purposes. Never exploit the scripts as a spam bot.

  8. Playing with MNIST

    A hand-written digit recognizer (with a very low accuracy now) via machine learning with MNIST dataset.