Create app.py

app.py

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+import torch
+from transformers import AutoTokenizer, VitsModel
+import gradio as gr
+import soundfile as sf
+import tempfile
+
+# Load Meta's MMS-TTS model for Min Nan (zh-nan)
+model = VitsModel.from_pretrained("facebook/mms-tts-nan")
+tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-nan")
+
+# Synthesize speech from Min Nan (POJ) text input
+def synthesize(text):
+    inputs = tokenizer(text, return_tensors="pt")
+    with torch.no_grad():
+        output = model(**inputs)
+    audio = output.waveform.squeeze().cpu().numpy()
+
+    # Use model-defined sampling rate for writing audio
+    sampling_rate = model.config.sampling_rate
+    tmp_wav = tempfile.NamedTemporaryFile(suffix=".wav", delete=False)
+    sf.write(tmp_wav.name, audio, samplerate=sampling_rate)
+    return tmp_wav.name
+
+# Gradio app interface
+demo = gr.Interface(
+    fn=synthesize,
+    inputs=gr.Textbox(
+        lines=3,
+        placeholder="Enter Min Nan (Taiwanese Hokkien) text in POJ format.\nExample: Lí hó! Góa sī lâng Tâi-oân.",
+        label="Min Nan Text (POJ format)"
+    ),
+    outputs=gr.Audio(type="filepath", label="Synthesized Speech"),
+    title="Text-to-Speech (TTS) for Min Nan / Taiwanese Hokkien using Meta’s MMS-TTS Model (facebook/mms-tts-nan)",
+    description=(
+        "🗣️ This application uses Meta's multilingual speech model (MMS-TTS) to generate natural speech "
+        "from text written in Min Nan Chinese (zh-nan), also known as Taiwanese Hokkien. "
+        "Input text should be written using the Pe̍h-ōe-jī (POJ) romanization system. \n\n"
+        "Example input: Lí hó! Góa sī lâng Tâi-oân.\n\n"
+        "The output is a 16kHz WAV audio file synthesized using the VITS-based neural TTS model."
+    ),
+    allow_flagging="never"
+)
+
+if __name__ == "__main__":
+    demo.launch()