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Article-22388-Telegram-Voice-Trading-MT5-Accessibility

This repository is an article-derived reference project based on the original MQL5 article. It does not claim to reproduce the full original source code unless files are explicitly attached.

Overview

This project documents a semi-automated remote voice-command trading pipeline for MetaTrader 5. The architecture links a Telegram voice message to a local Python middleware, which transcribes and parses the message, exposes commands over HTTP, and lets an MQL5 Expert Advisor poll, execute, and return results.

The design targets low-bandwidth remote control and accessibility use cases, especially when the trader is away from the desktop terminal.

Original Article

Repository Purpose

This repository serves as a reference reconstruction of the solution described in the article:

  • a Python middleware that combines:
  • Telegram bot polling
  • voice-note download and conversion
  • speech-to-text transcription
  • natural-language command parsing
  • local HTTP server endpoints
  • an MQL5 Expert Advisor that:
  • polls the middleware with WebRequest
  • parses JSON commands
  • executes trades through CTrade
  • posts execution results back to the middleware

It is useful as a study reference for:

  • Telegram-to-MT5 integration
  • pull-based command delivery in MQL5
  • low-bandwidth remote trade control
  • accessibility-oriented trading workflows

Key Concepts

  • Pull-based HTTP polling from MQL5
  • Telegram voice-note handling
  • Speech recognition via Python
  • Audio conversion with ffmpeg and pydub
  • JSON-based command exchange
  • Cross-language integration between Python and MQL5
  • Remote order execution with CTrade
  • Simple in-memory queueing and result synchronization
  • Risk reduction through default micro-lot sizing

Algorithm / Architecture Summary

  1. A user sends a Telegram voice message.
  2. The Python bot downloads the .ogg file.
  3. The middleware converts audio to 16 kHz mono WAV.
  4. Speech is transcribed using Python speech recognition.
  5. Parsed text is converted into a JSON command such as:
  • BUY
  • SELL
  • CLOSE_ALL
  • BALANCE
  1. The command is placed into an in-memory queue.
  2. The MQL5 EA polls GET /get_command every 2 seconds.
  3. If a command is available, the EA:
  • parses JSON using JAson.mqh
  • executes the requested action
  • builds a JSON response
  1. The EA sends the result to POST /post_response.
  2. The Telegram bot returns the outcome to the user.

Important implementation note highlighted in the article:

  • StringToCharArray in MQL5 appends a null terminator, which must be stripped before POSTing JSON to Python.

Mentioned or Attached Files

Explicitly attached files

  • telegram_trading_bot.py — Python 3 middleware script
  • OvercomingAccessibilityIV.mq5 — MQL5 Expert Advisor
  • JAson.mqh / Jason.mqh — third-party JSON parser referenced from MQL5 CodeBase

Mentioned in text

  • MQL5\Include\OvercomingAccessibilityIV\JAson.mqh
  • MQL5\Experts\OvercomingAccessibilityIV.mq5

Statistics

  • Polling interval: 2 seconds
  • Typical round-trip latency: 1.5-4.2 seconds
  • HTTP round-trip + trade execution: 50-200 ms
  • Bandwidth per poll request: ~200 bytes
  • Empty queue response size: ~20 bytes
  • Full trade cycle bandwidth: less than 30 KB
  • Voice download size: ~10-30 KB
  • Python version: 3.10+
  • HTTP server bind address: 127.0.0.1:8082

Tags

MQL5 MetaTrader5 Telegram Python WebRequest Voice-Control Accessibility JSON CTrade Speech-Recognition

Difficulty

Intermediate

Requires familiarity with:

  • MQL5 Expert Advisor development
  • Python environment setup
  • HTTP/JSON communication
  • Telegram bot configuration
  • Windows dependency setup for ffmpeg

Limitations

  • This is an article-derived reference project; the README reflects the article content and attached file list.
  • Full original repository structure is not available unless the attached files are actually present in this processed input.
  • The solution depends on a continuously running Windows machine with MetaTrader 5 open.
  • The architecture uses polling, so execution latency includes the polling interval.
  • The speech recognition path described in the article uses external Google STT through Python libraries.
  • The JSON parser include is third-party and must be obtained separately if not bundled.
  • If no attached source files are present in this repository snapshot, then no attached source files were available in the processed input.

Reference