Description

LiteWebSynth is a synthesizer with GM|GS|XG instrumental sound fonts. The sequencer processes two types of MIDI files: 0 and 1. All GM timbres are generated by a combination of oscillators and a dynamically generated BufferSource. Some of the synthesizer’s audio nodes have controls located on the front panel. The built-in oscilloscope displays the actual waveform of the synthesizer’s resulting signal, the AHDSR envelope shape, and the current RAM usage of the user’s local computer. The GM Timbre Editor and GS|XG SoundFonts Editor allow you to adjust sound parameters. The GM|GS|XG diagram shows the current configuration of the synthesizer’s audio nodes. The LiteWebSynth plugin is created using AI.
P.S.: After experimenting, I concluded that when creating a .mid file, the PPQN parameter should be a multiple of 4.

For the end user: There is a small Help section located under: Sequencer/Help.

You can test this plugin on its https://adminkov.bcr.by/midi/

You can send a letter to the developer at: klenitskiy.oleg@mail.ru

External Services

This plugin integrates with third-party services to provide advanced audio processing and conversion features. Data is transmitted to these external servers only when the user explicitly triggers the respective functionality.

This plugin integrates with third-party services to provide advanced audio processing, conversion, and recognition features. Data is transmitted to external servers or handled locally based on the specific functionality triggered by the user.

API2Convert

* Purpose: Converts MIDI files into various audio formats.
* Data transmitted: The source MIDI file and the user’s custom API key.
* Trigger: Data is sent to the external server only when the user explicitly clicks the “Export” button.
* Service Provider: API2Convert (https://api2convert.com)
* Terms of Service: https://online-convert.com/terms
* Privacy Policy: https://online-convert.com/privacy

TensorFlow (Local AI Processing)

* Purpose: Converts WAV/MP3 audio files into MIDI format using machine learning models.
* Data transmitted: None. The audio file is processed locally in the user’s browser via the TensorFlow library. No media files are uploaded to external servers.
* External Resource: The TensorFlow core JavaScript library is loaded from Cloudflare CDN.
* Terms of Service: https://developers.google.com/terms/site-policies
* Open Source License: https://www.apache.org/licenses/LICENSE-2.0

Spotify Audio Intelligence Lab (Basic Pitch)

* Purpose: Provides the core machine learning models to convert WAV/MP3 audio files into MIDI format.
* Data transmitted: None. The AI models (model.json and weights) are hosted locally within the plugin directory and executed entirely in the user’s browser. No data is shared with Spotify servers.
* Open Source Project: https://github.com/spotify/basic-pitch
* Open Source License: https://www.apache.org/licenses/LICENSE-2.0