---
title: Mandarin Tone Evaluation
emoji: 📉
colorFrom: gray
colorTo: blue
sdk: gradio
sdk_version: 4.7.1
app_file: app.py
pinned: false
---

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

# Team 3 Project - Tone Evaluation

## Overview

Welcome to Team 3's Tone Evaluation project! This repository contains the necessary files and resources for our project, which focuses on data processing, training, testing, and a user interface (UI) demo.

## Project Structure

- **Data Processing File**: [dataset.py](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation/blob/main/dataset.py)
  - This script is responsible for processing the raw data and preparing it for training and testing.
  - It takes input audio in wav format, and transfer audio into mel spectrum form and fundamental frequency form. These will be the two main features for the model to analyze.
  - We convert the pinyin and tone into numerical lables by providing a text file and link each pinyin to a index.

- **Train File**: [train.py](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation/blob/main/train.py)
  - This file contains the code for training our tone evaluation model. We use CNN+CTC model for this task. 

- **Test File**: [test.py](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation/blob/main/test.py)
  - Use this script to evaluate the performance of our trained model on test data.
  - Currenty, we set the model to only accepct wav format audio, and after loading the audio, model will predict the tone sequence for the sentence.

- **UI Demo**: [ui_space](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation)
  - Explore the user interface demo to interact with the tone evaluation model.
  - You can upload wav format audio to our UI and see the evaluation result. We also provided some audio files for you to directly use.

## Dataset

We provide two versions of the dataset:

- **Full Size Version**: Download from Kaggle [full_dataset](https://huggingface.co/datasets/CS5647Team3/full_dataset)
- **Small Size Zip Version**: Zip file, Download from [data_mini](https://huggingface.co/datasets/CS5647Team3/data_mini)

Additionally, we offer a text file for Pinyin encoding: [pinyin.txt](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation/blob/main/pinyin.txt). This file is crucial for understanding the encoding used in our dataset.

## Getting Started

Follow these steps to get started with our project:

1. Clone this repository to your local machine.
2. Run the data processing script: `python data_processing.py`
3. Train the model using: `python train.py`
4. Evaluate the model with: `python test.py`
5. Explore the UI demo: `python ui_demo.py`

## Additional Information


- If you encounter any issues or have questions, feel free to reach out to our team through emails.
- Dataset and preprocessing
- Shen Siyan shen_siyan@u.nus.edu
- Ouyang Yanjia e0954791@u.nus.edu
- Model Training
- Zhao Zhengkai
- zhaozhengkai@u.nus.edu
- Liu Mingxuan
- e0917087@u.nus.edu

We hope you find our project useful and insightful! Happy coding!