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--- |
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title: Mandarin Tone Evaluation |
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emoji: 📉 |
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colorFrom: gray |
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colorTo: blue |
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sdk: gradio |
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sdk_version: 4.7.1 |
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app_file: app.py |
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pinned: false |
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--- |
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |
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# Team 3 Project - Tone Evaluation |
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## Overview |
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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. |
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## Project Structure |
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- **Data Processing File**: [dataset.py](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation/blob/main/dataset.py) |
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- This script is responsible for processing the raw data and preparing it for training and testing. |
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- 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. |
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- We convert the pinyin and tone into numerical lables by providing a text file and link each pinyin to a index. |
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- **Train File**: [train.py](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation/blob/main/train.py) |
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- This file contains the code for training our tone evaluation model. We use CNN+CTC model for this task. |
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- **Test File**: [test.py](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation/blob/main/test.py) |
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- Use this script to evaluate the performance of our trained model on test data. |
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- 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. |
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- **UI Demo**: [ui_space](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation) |
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- Explore the user interface demo to interact with the tone evaluation model. |
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- 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. |
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## Dataset |
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We provide two versions of the dataset: |
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- **Full Size Version**: Download from Kaggle [full_dataset](https://huggingface.co/datasets/CS5647Team3/full_dataset) |
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- **Small Size Zip Version**: Zip file, Download from [data_mini](https://huggingface.co/datasets/CS5647Team3/data_mini) |
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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. |
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## Getting Started |
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Follow these steps to get started with our project: |
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1. Clone this repository to your local machine. |
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2. Run the data processing script: `python data_processing.py` |
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3. Train the model using: `python train.py` |
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4. Evaluate the model with: `python test.py` |
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5. Explore the UI demo: `python ui_demo.py` |
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## Additional Information |
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- If you encounter any issues or have questions, feel free to reach out to our team through emails. |
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- Dataset and preprocessing |
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- Shen Siyan shen[email protected] |
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- Ouyang Yanjia [email protected] |
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- Model Training |
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- Zhao Zhengkai |
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- [email protected] |
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- Liu Mingxuan |
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- [email protected] |
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We hope you find our project useful and insightful! Happy coding! |
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