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Duplicate from Has-ai/text-speech
Browse filesCo-authored-by: Hasmit Singla <[email protected]>
- .gitattributes +34 -0
- README.md +13 -0
- app.py +92 -0
- requirements.txt +5 -0
- setup.cfg +12 -0
.gitattributes
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README.md
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---
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title: Text Speech
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emoji: 🏆
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colorFrom: yellow
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colorTo: yellow
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sdk: gradio
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sdk_version: 3.29.0
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app_file: app.py
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pinned: false
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duplicated_from: Has-ai/text-speech
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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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app.py
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import logging
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from typing import cast
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import gradio as gr
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from balacoon_tts import TTS
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from huggingface_hub import hf_hub_download, list_repo_files
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# global tts module, initialized from a model selected
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tts = None
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def main():
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logging.basicConfig(level=logging.INFO)
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with gr.Blocks() as demo:
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gr.Markdown(
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"""
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<h1 align="center">Clone your voice</h1>
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1. Write an utterance to generate,
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2. Select the model to synthesize with
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3. Select speaker
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4. Hit "Generate" and listen to the result!
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When you select model for the first time,
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it will take a little time to download it.
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"""
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)
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with gr.Row(variant="panel"):
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text = gr.Textbox(label="Text", placeholder="Type something here...")
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with gr.Row():
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with gr.Column(variant="panel"):
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repo_files = list_repo_files(repo_id="balacoon/tts")
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model_files = [x for x in repo_files if x.endswith("_cpu.addon")]
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model_name = gr.Dropdown(
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label="Model",
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choices=model_files,
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)
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with gr.Column(variant="panel"):
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speaker = gr.Dropdown(label="Speaker", choices=[])
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def set_model(model_name_str: str):
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"""
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gets value from `model_name`, loads model,
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re-initializes tts object, gets list of
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speakers that model supports and set them to `speaker`
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"""
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model_path = hf_hub_download(
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repo_id="balacoon/tts", filename=model_name_str
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)
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global tts
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tts = TTS(model_path)
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speakers = tts.get_speakers()
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value = speakers[-1]
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return gr.Dropdown.update(
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choices=speakers, value=value, visible=True
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)
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model_name.change(set_model, inputs=model_name, outputs=speaker)
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with gr.Row(variant="panel"):
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generate = gr.Button("Generate")
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with gr.Row(variant="panel"):
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audio = gr.Audio()
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def synthesize_audio(text_str: str, speaker_str: str = ""):
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"""
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gets utterance to synthesize from `text` Textbox
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and speaker name from `speaker` dropdown list.
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speaker name might be empty for single-speaker models.
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Synthesizes the waveform and updates `audio` with it.
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"""
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if not text_str:
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logging.info("text or speaker are not provided")
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return None
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global tts
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if len(text_str) > 1024:
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text_str = text_str[:1024]
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samples = cast(TTS, tts).synthesize(text_str, speaker_str)
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return gr.Audio.update(value=(cast(TTS, tts).get_sampling_rate(), samples))
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generate.click(synthesize_audio, inputs=[text, speaker], outputs=audio)
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demo.launch()
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if __name__ == "__main__":
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main()
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requirements.txt
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--index-url https://pypi.fury.io/balacoon/
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--extra-index-url https://pypi.org/simple/
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balacoon-tts==0.1.1
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huggingface_hub
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numpy
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setup.cfg
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[flake8]
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max_complexity=10
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per-file-ignores=__init__.py:F401,F403
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ignore = E203,W503
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max-line-length=119
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[isort]
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profile=black
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line_length=119
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[mypy]
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ignore_missing_imports = True
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