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import spaces |
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import gradio as gr |
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import os |
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from whisperspeech.pipeline import Pipeline |
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import torch |
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import torch.nn.functional as F |
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from whisperspeech.languages import LANGUAGES |
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from whisperspeech.pipeline import Pipeline |
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import tempfil |
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title = """#🙋🏻♂️ Welcome to🌟Tonic's🌬️💬📝WhisperSpeech |
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You can use this ZeroGPU Space to test out the current model [🌬️💬📝collabora/whisperspeech](https://huggingface.co/collabora/whisperspeech). 🌬️💬📝collabora/whisperspeech is An Open Source text-to-speech system built by inverting Whisper. Previously known as spear-tts-pytorch. It's like Stable Diffusion but for speech – both powerful and easily customizable. |
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You can also use 🌬️💬📝WhisperSpeech by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic/laion-whisper?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3> |
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Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community 👻 [](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [Poly](https://github.com/tonic-ai/poly) 🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗 |
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""" |
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@spaces.GPU |
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def whisper_speech_demo(text, lang, speaker_audio=None, mix_lang=None, mix_text=None): |
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pipe = Pipeline(s2a_ref='collabora/whisperspeech:s2a-q4-tiny-en+pl.model') |
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speaker_url = None |
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if speaker_audio is not None: |
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speaker_url = speaker_audio.name |
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if mix_lang and mix_text: |
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mixed_langs = lang.split(',') + mix_lang.split(',') |
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mixed_texts = [text] + mix_text.split(',') |
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stoks = pipe.t2s.generate(mixed_texts, lang=mixed_langs) |
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audio_data = pipe.generate(stoks, speaker_url, lang=mixed_langs[0]) |
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else: |
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audio_data = pipe.generate(text, speaker_url, lang) |
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with tempfile.NamedTemporaryFile(delete=False, suffix='.wav') as tmp_file: |
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tmp_file_name = tmp_file.name |
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with open(tmp_file_name, 'wb') as file: |
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file.write(audio_data) |
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return tmp_file_name |
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with gr.Blocks() as demo: |
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gr.Markdown(title) |
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with gr.Row(): |
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text_input = gr.Textbox(label="Enter text") |
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lang_input = gr.Dropdown(choices=list(LANGUAGES.keys()), label="Language") |
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speaker_input = gr.File(label="Upload Speaker Audio (optional)", type="file", accepts=["audio/*"]) |
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with gr.Row(): |
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mix_lang_input = gr.Textbox(label="Mixed Languages (optional, comma-separated)", placeholder="e.g., en,pl") |
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mix_text_input = gr.Textbox(label="Mixed Texts (optional, for mixed languages)", placeholder="e.g., Hello, Cześć") |
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with gr.Row(): |
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submit_button = gr.Button("Generate Speech") |
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output_audio = gr.Audio(label="Generated Speech") |
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submit_button.click( |
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whisper_speech_demo, |
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inputs=[text_input, lang_input, speaker_input, mix_lang_input, mix_text_input], |
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outputs=output_audio |
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) |
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demo.launch() |
