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AI Pronunciation Trainer

AI Pronunciation Trainer is a Python web application for practising language pronunciation by speaking text and receiving AI-generated evaluation. It uses speech recognition, with Whisper as its standard ASR model, and allows the practice text to be edited before evaluation.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

AI Pronunciation Trainer — OpenViST project profile in Audio & Voice AI.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it for self-directed pronunciation practice when you want automated feedback on spoken text, or when you need a documented Python starting point for a self-hosted trainer.

Who it is for

  • Language learners seeking automated feedback during spoken-pronunciation practice.
  • Developers who want to run or modify an open-source pronunciation trainer.

Documented uses

  • Practise saying prompted text and receive pronunciation evaluation.
  • Edit the practice text before speaking and evaluating it.
  • Run the trainer locally from its Python source.
  • Adapt the application for another language through code and language-specific resources.
Before you choose

Requirements & limits

The README says the hosted version is recommended for desktop Chrome, with other browsers not officially supported, and that online usage is limited by day. Local use requires Python dependencies and ffmpeg. The repository is public under the AGPL-3.0 license.

  • Whisper is the standard ASR model described in the README.
  • The online version has a daily usage limit; local setup is an alternative for users able to install the requirements and ffmpeg.
  • Adding another language requires code and language-specific resources; languages unsupported by Whisper need an integrated compatible speech-to-text model.
  • The project documentation cautions that bugs may occur.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Run the web application locally

Install the project requirements and start its local web application.

Before you start

  • A recent Python 3.x version
  • The project repository and its requirements.txt file
  • ffmpeg; on Windows, its bin folder may need to be added to PATH

Steps

  1. Install the Python dependencies with pip install -r requirements.txt.

  2. Install ffmpeg for your operating system.

  3. Run python webApp.py to start the application locally.

Expected outcome

The local Python web application starts using the project’s documented entry point.

Guide limitations

  • The README describes the setup as expected to work with a recent Python 3.x version; it does not guarantee compatibility.
  • This guide covers local startup, not a particular pronunciation-evaluation session.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
14 October 2026
Original website title
Thiagohgl/ai-pronunciation-trainer · Official homepage title · retained in its source language
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