Spaces:
Running
on
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Running
on
Zero
Commit
·
69b575f
1
Parent(s):
2d772b8
Add initial implementation of Egyptian-Arabic TTS with Gradio interface
Browse files- app.py +80 -0
- requirements.txt +7 -0
app.py
ADDED
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import torch
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from TTS.tts.configs.xtts_config import XttsConfig
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from TTS.tts.models.xtts import Xtts
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from pathlib import Path
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import gradio as gr
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import spaces
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CONFIG_URL = 'https://huggingface.co/OmarSamir/EGTTS-V0.1/resolve/main/config.json'
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VOCAB_URL = 'https://huggingface.co/OmarSamir/EGTTS-V0.1/resolve/main/vocab.json'
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MODEL_URL = 'https://huggingface.co/OmarSamir/EGTTS-V0.1/resolve/main/model.pth'
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SPEAKER_AUDIO_URL = 'https://huggingface.co/OmarSamir/EGTTS-V0.1/resolve/main/speaker_reference.wav'
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base_path = Path(__file__).parent
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# Download the files into the base_path
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config_path = base_path / 'config.json'
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if not config_path.exists():
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torch.hub.download_url_to_file(CONFIG_URL, config_path)
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vocab_path = base_path / 'vocab.json'
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if not vocab_path.exists():
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torch.hub.download_url_to_file(VOCAB_URL, vocab_path)
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model_path = base_path / 'model.pth'
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if not model_path.exists():
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torch.hub.download_url_to_file(MODEL_URL, model_path)
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speaker_audio_path = base_path / 'speaker_reference.wav'
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if not speaker_audio_path.exists():
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torch.hub.download_url_to_file(SPEAKER_AUDIO_URL, speaker_audio_path)
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config_path = str(config_path)
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vocab_path = str(vocab_path)
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model_path = str(model_path.parent)
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speaker_audio_path = str(speaker_audio_path)
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print("Loading model...")
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device = "cuda" if torch.cuda.is_available() else "cpu"
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config = XttsConfig()
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config.load_json(config_path)
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model = Xtts.init_from_config(config)
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model.load_checkpoint(config, checkpoint_dir=model_path, use_deepspeed=True, vocab_path=vocab_path)
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model.to(device)
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@spaces.GPU
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def infer_EGTTS(text: str, speaker_audio_path: str, temperature: float = 0.75):
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print("Computing speaker latents...")
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gpt_cond_latent, speaker_embedding = model.get_conditioning_latents(audio_path=[speaker_audio_path])
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print("Inference...")
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out = model.inference(
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text,
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"ar",
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gpt_cond_latent,
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speaker_embedding,
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temperature=temperature,
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)
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return 24000, out["wav"]
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header = """<h1 style="text-align:center">Egyptian-Arabic-TTS (EGTTS)</h1>
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## Instructions:
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1. Enter the text you want to synthesize.
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2. Upload a 4-5 seconds audio file of the speaker you want to clone.
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3. Click on the "Generate" button.
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**This space was only possible because of the amazing work done by [OmarSamir](https://huggingface.co/OmarSamir) on the [EGTTS](https://huggingface.co/OmarSamir/EGTTS-V0.1) model.**
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"""
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with gr.Blocks(title="EGTTS") as app:
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gr.Markdown(header)
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with gr.Row():
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with gr.Column():
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text = gr.Textbox(label="Text to synthesize", value="السلام عليكم ورحمة الله")
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speaker_refrence = gr.Audio(label="Speaker reference", value=speaker_audio_path, type="filepath")
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temperature = gr.Slider(label="Temperature", min_value=0.1, max_value=1.0, value=0.75, step=0.05)
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generate_btn = gr.Button(value="Generate", variant="primary")
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output = gr.Audio(label="Synthesized audio")
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generate_btn.click(infer_EGTTS, inputs=[text, speaker_refrence, temperature], outputs=output)
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app.launch()
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requirements.txt
ADDED
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git+https://github.com/coqui-ai/TTS
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transformers
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deepspeed
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torch
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torchaudio
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spaces
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gradio
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