Update README.md

README.md

@@ -1,74 +1,77 @@
-<div align="center">
-<p align="center">
-  <h2>DeepAudio-V1</h2>
-  <a href="https://arxiv.org/">Paper</a> | <a href="https://pages.github.com/">Webpage</a> | <a href="https://huggingface.co/">Models</a>
-</p>
-</div>
-
-
-## [DeepAudio-V1:Towards Multi-Modal Multi-Stage End-to-End Video to Speech and Audio Generation](https://pages.github.com/)
-
-
-## Installation
-
-**1. Create a conda environment**
-
-```bash
-conda create -n v2as python=3.10
-conda activate v2as
-```
-
-**2. F5-TTS base install**
-
-```bash
-cd ./F5-TTS
-pip install -e .
-```
-
-**3. Additional requirements**
-
-```bash
-pip install -r requirements.txt
-conda install cudnn
-```
-
-**Pretrained models**
-
-The models are available at https://huggingface.co/. See [MODELS.md](./MODELS.md) for more details.
-
-## Inference
-
-**1. V2A inference**
-
-```bash
-bash v2a.sh
-```
-
-**2. V2S inference**
-
-```bash
-bash v2s.sh
-```
-
-**3. TTS inference**
-
-```bash
-bash tts.sh
-```
-
-## Evaluation
-
-```bash
-bash eval_v2c.sh
-```
-
-
-## Acknowledgement
-
-- [MMAudio](https://github.com/hkchengrex/MMAudio) for video-to-audio backbone and pretrained models
-- [F5-TTS](https://github.com/SWivid/F5-TTS) for text-to-speech and video-to-speech backbone
-- [V2C](https://github.com/chenqi008/V2C) for animated movie benchmark
-- [Wav2Vec2-Emotion](https://huggingface.co/audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim) for emotion recognition in EMO-SIM evaluation.
-- [WavLM-SV](https://huggingface.co/microsoft/wavlm-base-sv) for speech recognition in SPK-SIM evaluation.
-- [Whisper](https://huggingface.co/Systran/faster-whisper-large-v3) for speech recognition in WER evaluation.
-
+---
+title: DeepAudio-V1 — multi-modal speech and audio generation
+emoji: 🔊
+colorFrom: blue
+colorTo: indigo
+sdk: gradio
+app_file: app.py
+pinned: false
+---
+
+
+## [DeepAudio-V1:Towards Multi-Modal Multi-Stage End-to-End Video to Speech and Audio Generation](https://pages.github.com/)
+
+
+## Installation
+
+**1. Create a conda environment**
+
+```bash
+conda create -n v2as python=3.10
+conda activate v2as
+```
+
+**2. F5-TTS base install**
+
+```bash
+cd ./F5-TTS
+pip install -e .
+```
+
+**3. Additional requirements**
+
+```bash
+pip install -r requirements.txt
+conda install cudnn
+```
+
+**Pretrained models**
+
+The models are available at https://huggingface.co/. See [MODELS.md](./MODELS.md) for more details.
+
+## Inference
+
+**1. V2A inference**
+
+```bash
+bash v2a.sh
+```
+
+**2. V2S inference**
+
+```bash
+bash v2s.sh
+```
+
+**3. TTS inference**
+
+```bash
+bash tts.sh
+```
+
+## Evaluation
+
+```bash
+bash eval_v2c.sh
+```
+
+
+## Acknowledgement
+
+- [MMAudio](https://github.com/hkchengrex/MMAudio) for video-to-audio backbone and pretrained models
+- [F5-TTS](https://github.com/SWivid/F5-TTS) for text-to-speech and video-to-speech backbone
+- [V2C](https://github.com/chenqi008/V2C) for animated movie benchmark
+- [Wav2Vec2-Emotion](https://huggingface.co/audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim) for emotion recognition in EMO-SIM evaluation.
+- [WavLM-SV](https://huggingface.co/microsoft/wavlm-base-sv) for speech recognition in SPK-SIM evaluation.
+- [Whisper](https://huggingface.co/Systran/faster-whisper-large-v3) for speech recognition in WER evaluation.
+