update readme

README.md

@@ -1,38 +1,13 @@
-# MOS Evaluation Application
-
-## Introduction
-This application is designed for Mean Opinion Score (MOS) evaluation of audio samples.
-
-## Installation
-1. Set up a Conda environment.
-2. Install the required dependencies by running:
-
-```shell
-pip install -r requirements.txt
-```
-
-## Quick Start
-
-To launch the application, execute:
-```shell
-python app.py
-```
-
-Evaluation results will be saved into `results` directory.
-
-## Data Preparation
-Before running the application, prepare a folder containing `N` CSV files, where `N` is the number of participants expected to perform evaluations.
-
-Each CSV file should have four columns with `n` rows (`n` can vary between files):
-- `filepath`: Path to the audio file being evaluated.
-- `gt`: Ground-truth audio corresponding to `filepath`.
-- `model`: The model that generated `filepath`.
-- `transcript`: Ground-truth transcript of `filepath`.
-
-Refer to the sample in the [data](./samples/data) directory.
-
-## How Does This Tool Work?
-
-The `MOSApp` class in `app.py` loads and stores each CSV file as an attribute. When users enter their IDs, the application automatically assigns a unique CSV file to each user, ensuring that no two users evaluate the same file.
-
-Each user's progress is saved in the `progress` directory. If a user returns to finish their evaluation and enters the same ID as before, their previous progress will be automatically restored.
+---
+title: DiFlow TTS
+emoji: 👀
+colorFrom: gray
+colorTo: indigo
+sdk: gradio
+sdk_version: 5.38.0
+app_file: app.py
+pinned: false
+short_description: MOS Evaluation
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference