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import torch
import gradio as gr
import torchaudio
from transformers import SpeechT5Processor, SpeechT5ForTextToSpeech
from transformers.models.speecht5 import SpeechT5HifiGan
processor = SpeechT5Processor.from_pretrained("nambn0321/T5_US_Accent_1")
model = SpeechT5ForTextToSpeech.from_pretrained("nambn0321/T5_US_Accent_1", use_safetensors=True, trust_remote_code=True)
vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan")
device = "cuda" if torch.cuda.is_available() else "cpu"
model = model.to(device)
vocoder = vocoder.to(device)
speaker_embedding = torch.tensor([[-0.0743, -0.0103, 0.0260, 0.0237, 0.0045, -0.0173, -0.0721, -0.0579,
0.0374, 0.0206, -0.0648, -0.0665, 0.0259, 0.0414, 0.0323, 0.0512,
-0.0078, 0.0259, 0.0123, 0.0155, 0.0371, 0.0255, -0.0156, -0.0398,
-0.0612, -0.0098, -0.0582, -0.0046, 0.0377, 0.0320, -0.0028, 0.0450,
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-0.0551, 0.0721, 0.0228, 0.0490, 0.0465, 0.0149, -0.0871, -0.0100,
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0.0376, 0.0224, 0.0141, -0.0388, -0.0615, -0.0467, 0.0216, 0.0115,
0.0205, 0.0136, 0.0419, 0.0258, 0.0181, 0.0173, -0.0678, -0.0821,
-0.0862, -0.0480, -0.0566, -0.0387, -0.0345, -0.0636, -0.0453, 0.0519,
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0.0200, 0.0304, -0.0486, -0.0640, 0.0396, -0.1017, -0.0794, 0.0478,
0.0425, -0.0547, 0.0486, 0.0480, 0.0169, 0.0227, -0.0807, 0.0313,
0.0611, -0.0058, 0.0498, 0.0242, -0.0534, -0.0267, -0.0341, -0.0348,
0.0220, -0.0662, 0.0370, 0.0365, -0.0660, 0.0279, -0.0644, 0.0143,
0.0326, 0.0500, 0.0300, 0.0072, 0.0336, 0.0345, 0.0276, -0.0646,
-0.0484, -0.0059, -0.0605, 0.0012, 0.0081, 0.0036, -0.0033, 0.0463,
-0.0506, 0.0270, -0.0066, -0.0609, 0.0493, -0.1155, 0.0447, -0.0371,
-0.0567, 0.0285, 0.0146, 0.0203, 0.0108, -0.0639, -0.0762, 0.0279,
0.0205, 0.0018, 0.0158, -0.0595, -0.0299, 0.0084, 0.0270, 0.0379,
0.0132, 0.0510, 0.0261, -0.0636, 0.0276, -0.0498, 0.0167, 0.0027,
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-0.0659, 0.0478, 0.0131, 0.0165, 0.0172, 0.0042, 0.0322, -0.0516,
0.0523, 0.0285, -0.0554, 0.0056, -0.0021, 0.0150, 0.0391, -0.0400,
0.0248, -0.0332, 0.0047, -0.0792, -0.0429, 0.0398, -0.0565, 0.0409,
0.0457, -0.0870, 0.0314, 0.0226, -0.0816, 0.0377, -0.0779, -0.0134,
0.0412, 0.0425, 0.0585, 0.0799, 0.0527, 0.0279, -0.0557, 0.0240,
0.0306, -0.0370, 0.0098, -0.0225, 0.0299, 0.0527, -0.0011, 0.0456,
-0.0768, 0.0237, -0.0966, 0.0106, -0.0521, 0.0512, 0.0424, 0.0236,
0.0301, 0.0044, 0.0502, 0.0307, 0.0095, -0.0570, 0.0166, 0.0166,
0.0321, 0.0367, -0.0677, 0.0514, 0.0165, -0.0601, 0.0407, 0.0401,
0.0020, 0.0015, 0.0574, 0.0310, -0.0053, -0.0610, 0.0391, -0.0212,
0.0271, -0.0256, -0.0613, 0.0301, 0.0564, 0.0209, -0.0815, -0.0544,
-0.0091, 0.0303, 0.0256, -0.0597, -0.0593, 0.0376, 0.0184, 0.0580,
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0.0303, 0.0400, 0.0267, 0.0290, 0.0309, 0.0488, 0.0430, 0.0153,
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-0.0568, 0.0611, -0.0643, 0.0084, 0.0148, -0.0675, 0.0311, 0.0652,
-0.0648, -0.0791, -0.0660, 0.0231, 0.0096, 0.0477, -0.0702, 0.0503,
0.0446, -0.0523, -0.0305, -0.0593, 0.0238, -0.0557, 0.0130, 0.0067,
-0.0756, 0.0354, 0.0289, 0.0261, -0.0466, -0.0584, -0.0441, -0.0355,
-0.0699, 0.1035, 0.0268, -0.0459, -0.0062, 0.0283, -0.0462, 0.0247,
-0.1061, 0.0222, -0.0052, 0.0058, 0.0479, -0.0126, -0.0533, 0.0160,
0.0042, 0.0476, 0.0133, 0.0263, -0.0822, 0.0167, -0.0129, -0.0026,
0.0359, 0.0130, 0.0528, 0.0397, -0.0638, -0.1078, 0.0214, 0.0292,
0.0351, -0.0545, 0.0406, -0.0787, 0.0306, 0.0389, 0.0332, 0.0178,
-0.0405, 0.0238, 0.0087, 0.0140, 0.0397, -0.0856, -0.0334, -0.0002,
-0.0025, -0.0352, 0.0299, -0.0384, 0.0179, 0.0057, 0.0005, -0.0593,
-0.0505, -0.0592, -0.0831, 0.0174, 0.0417, -0.0128, 0.0286, -0.0422,
-0.0141, -0.0779, -0.1574, -0.0493, -0.0533, -0.0075, 0.0274, -0.0474,
-0.0516, 0.0257, 0.0360, 0.0330, 0.0212, -0.0346, -0.0637, -0.0165,
-0.0254, 0.0295, 0.0180, 0.0093, 0.0260, 0.0096, -0.0626, -0.0537,
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-0.0030, -0.0109, 0.0400, 0.0059, 0.0046, 0.0122, 0.0007, -0.0109,
0.0188, -0.0746, -0.0615, 0.0463, -0.0136, 0.0101, 0.0435, 0.0257,
-0.0516, 0.0282, 0.0218, -0.0788, 0.0135, 0.0192, -0.0027, 0.0225,
0.0103, 0.0045, -0.0529, -0.0672, 0.0158, -0.0058, 0.0440, 0.0572,
-0.0373, -0.0386, 0.0256, 0.0211, 0.0453, 0.0515, -0.0624, 0.0371,
-0.0205, -0.0121, -0.0542, 0.0136, -0.0411, 0.0284, 0.0219, -0.0009,
-0.0469, -0.0276, -0.0797, -0.0664, 0.0094, 0.0443, -0.0661, 0.0388,
-0.0244, -0.0143, -0.0674, 0.0379, 0.0583, -0.0234, 0.0413, -0.0651]]).to(device)
def tts_generate(text):
try:
# Preprocess input
inputs = processor(text=text, return_tensors="pt").to(device)
# Generate waveform directly with vocoder
with torch.no_grad():
waveform = model.generate_speech(
inputs["input_ids"],
speaker_embedding,
vocoder=vocoder
)
# Save waveform
output_path = "output.wav"
if waveform.dim() == 1:
waveform = waveform.unsqueeze(0)
torchaudio.save(output_path, waveform.cpu(), sample_rate=16000)
return output_path
except Exception as e:
print("Error during TTS generation:", e)
return "Error during speech synthesis."
demo = gr.Interface(
fn=tts_generate,
inputs=gr.Textbox(label="Enter text"),
outputs=gr.Audio(label="Generated Speech", type="filepath"),
title="SpeechT5 Text-to-Speech",
description="Enter text and hear it with my custom SpeechT5"
)
if __name__ == "__main__":
print("Launching Gradio demo")
demo.launch()
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