GAN训练用爬取MIDI文件中FF10/FF11非规范元事件问题咨询

Ah, those mysterious FF10 and FF11 meta events—been there, dealt with weird non-standard MIDI artifacts when scraping random files off the web too. Let’s break this down:

First, let’s ground this in the official MIDI spec: all standard meta events start with FF followed by a type byte in the range 00 to 7F. FF10 (hex) and FF11 fall way outside this standard range, which means they’re custom, non-standard meta events added by niche software, game MIDI engines, or custom tools—definitely not part of the official MIDI 1.0 or 2.0 specifications.

Why are these showing up? #

• They’re almost certainly added to track proprietary data: think custom track labels, application-specific expression controls, or even metadata tied to a specific sequencer or game. When scraping random MIDI files from the web, you’ll run into all sorts of these one-off extensions—creators love adding extra data that their own tools can use, even if it breaks strict spec compliance.
• Looking at your track header snippet: 4D 54 72 6B is the standard "MTrk" track marker, followed by 00 00 1A 8D which is a valid track length. The weird events are just buried later in the track’s event data.

How to handle them for your GAN training #

Since you’re focused on training a GAN with musical content (notes, velocities, CC messages, etc.), here’s the practical approach:

• Skip them entirely: These custom meta events don’t impact the actual musical performance. When parsing your MIDI files, whenever you hit an FF byte:
  1. Read the following type byte (10 or 11 in your case)
  2. Read the variable-length length field that comes next
  3. Jump ahead by that number of bytes and resume parsing standard events
• Optional: Log (but don’t overthink): If you’re curious, you can log the content of these events to check for patterns (e.g., are they always short text blobs? Do they repeat across files?). But for GAN training, this is unnecessary—your model doesn’t need this non-musical custom data.
• Don’t waste time "decoding" them: There’s no universal way to interpret these events unless you can track down the exact software that generated the files (unlikely when scraping random web data). Trying to reverse-engineer them will only slow down your workflow.

Quick parsing example (conceptual, using Python’s mido) #

If you’re using a library like mido, you can filter out unknown meta events with a simple check:

import mido

for msg in mido.MidiFile("your_scraped_midi.mid"):
    if msg.type == 'meta' and msg.meta_type not in mido.meta.META_TYPES:
        # Skip non-standard meta events like FF10/FF11
        continue
    # Process standard musical events here (Note On/Off, CC, etc.)

This will clean up your training data without losing any meaningful musical information.

内容的提问来源于stack exchange，提问作者steveeweeveewoo