Create app.py

app.py

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+import numpy as np
+import gradio as gr
+from scipy.io.wavfile import write
+from pydub import AudioSegment
+
+# Define the core Animalese function
+def animalese_synthesize(text, shorten=False, pitch=1.0):
+    def shorten_word(word):
+        if len(word) > 1:
+            return word[0] + word[-1]
+        return word
+
+    # Shorten words if the option is enabled
+    processed_script = text
+    if shorten:
+        processed_script = ''.join([shorten_word(w) for w in text.split()])
+
+    # Generate the waveform (This is a simplified version)
+    sample_rate = 44100
+    data = []
+    library_letter_secs = 0.15
+    library_samples_per_letter = int(library_letter_secs * sample_rate)
+    output_letter_secs = 0.075
+    output_samples_per_letter = int(output_letter_secs * sample_rate)
+
+    # Use a basic sine wave to simulate the sounds
+    for c in processed_script.upper():
+        if 'A' <= c <= 'Z':
+            freq = 440 + (ord(c) - ord('A')) * 10  # Simple mapping A-Z to frequencies
+            t = np.linspace(0, output_letter_secs, output_samples_per_letter, False)
+            wave = 0.5 * np.sin(2 * np.pi * freq * t * pitch)
+            data.extend(wave)
+        else:
+            data.extend([0] * output_samples_per_letter)
+
+    # Convert to numpy array and save as WAV
+    data = np.array(data, dtype=np.float32)
+    scaled = np.int16(data/np.max(np.abs(data)) * 32767)
+
+    return scaled, sample_rate
+
+def generate_wav_file(text, shorten, pitch):
+    data, sample_rate = animalese_synthesize(text, shorten, pitch)
+    output_file = "animalese_output.wav"
+    write(output_file, sample_rate, data)
+    return output_file
+
+# Define the Gradio interface
+def preview_audio(text, shorten, pitch):
+    output_file = generate_wav_file(text, shorten, pitch)
+    return output_file
+
+gr_interface = gr.Interface(
+    fn=preview_audio,
+    inputs=[
+        gr.Textbox(label="Text to Synthesize"),
+        gr.Checkbox(label="Shorten Words"),
+        gr.Slider(0.2, 2.0, step=0.1, label="Pitch", value=1.0)
+    ],
+    outputs=gr.Audio(label="Preview Animalese Audio")
+)
+
+if __name__ == "__main__":
+    gr_interface.launch()