File size: 9,673 Bytes
f3d10bd d2b5676 8d7e20b 7c03bdc f492d3b 5951a1a f492d3b 1cd841e 8d7e20b 08d90fe f3d10bd 2dc786b 08d90fe 2dc786b 0515d75 08d90fe 8aec1d9 2dc786b 0515d75 08d90fe c577d87 08d90fe d2b5676 8d7e20b c09f7ba 808fe78 c577d87 5b18578 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 | import torch
import gradio as gr
import torchaudio
from transformers import SpeechT5Processor, SpeechT5ForTextToSpeech
from transformers.models.speecht5 import SpeechT5HifiGan
processor = SpeechT5Processor.from_pretrained("microsoft/speecht5_tts")
model = SpeechT5ForTextToSpeech.from_pretrained("microsoft/speecht5_tts")
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.zeros(1, 512).to(device)
# processor = SpeechT5Processor.from_pretrained("nambn0321/TTS_with_T5_4")
# model = SpeechT5ForTextToSpeech.from_pretrained(
# "nambn0321/TTS_with_T5_4",
# 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([[-0.06632216, -0.02325863, 0.04376163, 0.01112046, -0.02864115,
# -0.03048201, -0.04865832, 0.00598873, 0.03105048, 0.01635859,
# -0.07552029, -0.09258246, 0.04839027, 0.04307159, 0.05019059,
# 0.05565156, 0.00533272, 0.0197331 , 0.01269842, 0.00576971,
# 0.02997943, 0.00765277, -0.01538683, -0.04164617, -0.05669912,
# -0.00767612, -0.05466911, 0.00988977, 0.05714991, 0.0216927 ,
# -0.00281803, 0.04948897, 0.04745187, -0.01738331, 0.03589115,
# -0.03788823, 0.03018526, 0.06933809, -0.01054026, -0.07338727,
# 0.01145766, -0.00347575, 0.02236829, 0.03353192, 0.01183521,
# -0.11246844, -0.01998361, 0.01333049, -0.08154028, 0.06184796,
# 0.04050031, 0.01181497, 0.0588 , 0.01634772, -0.11387676,
# -0.01355756, -0.01059065, 0.01194482, 0.03934296, 0.02436676,
# 0.00376559, -0.00813801, -0.01421188, -0.03595341, 0.02987706,
# 0.02612724, 0.03072971, -0.05161813, -0.06241557, -0.06545018,
# -0.00679519, 0.00900955, 0.03801987, 0.00294477, 0.02057374,
# 0.04256874, 0.00730863, -0.00282256, -0.05437343, -0.07569141,
# -0.07964483, -0.04049463, -0.06325456, -0.08040556, -0.03161319,
# -0.0557906 , -0.05558824, 0.05661038, 0.03932756, -0.00269612,
# 0.02999815, -0.05263155, 0.01048327, -0.05502405, 0.04730757,
# -0.03641531, 0.04466332, 0.04261209, -0.08965097, -0.06816243,
# 0.05328364, -0.0652955 , -0.09165341, 0.02487748, 0.04061233,
# 0.01143007, 0.04024159, 0.01869776, 0.02870329, 0.01503909,
# -0.07710361, 0.00802833, 0.07786133, -0.008355 , 0.02792075,
# 0.03834949, -0.07156748, 0.00127211, -0.05645351, 0.0293999 ,
# 0.03988929, -0.07301504, 0.01131906, 0.0415033 , -0.05863927,
# 0.0623733 , -0.07197598, 0.02887617, 0.03702732, 0.05255475,
# 0.03850314, 0.03016165, 0.04511765, 0.0400167 , 0.01042124,
# -0.08053102, -0.06103503, -0.02782067, -0.03948715, 0.00812866,
# -0.00215283, 0.00496819, -0.00270994, 0.04999355, -0.08324838,
# 0.01673055, -0.0224449 , -0.04158457, 0.03688109, -0.13497816,
# 0.02797874, -0.04349126, -0.06393341, 0.01634013, 0.00367471,
# 0.03441324, 0.00576339, -0.08563808, -0.08777589, 0.01206557,
# 0.01930428, 0.03046028, 0.00186808, 0.01118185, -0.06207091,
# 0.00285664, 0.04373416, 0.03865229, 0.02155851, 0.02963249,
# 0.03907783, -0.06465862, 0.00155482, -0.04207559, 0.02787214,
# 0.02055759, -0.05460549, -0.0024652 , 0.02217332, -0.07867457,
# 0.04810029, -0.0450572 , -0.01488631, 0.02080196, -0.07611465,
# -0.01182817, 0.03117848, 0.0593022 , -0.05042631, -0.06321163,
# 0.01080927, 0.03538311, -0.06461193, 0.02289902, 0.03690634,
# 0.02868471, 0.01077593, 0.00843379, 0.04739143, -0.03351105,
# 0.04080784, 0.01689551, -0.06830349, 0.01059405, 0.01843624,
# 0.01237972, 0.02619306, -0.02353077, 0.00792623, 0.02665057,
# 0.00471944, -0.08360166, -0.0301204 , 0.04510773, -0.03999252,
# 0.03273777, 0.02000749, -0.07822321, 0.04588151, 0.03334309,
# -0.09588112, 0.01911022, -0.06844518, -0.03093524, -0.02563222,
# 0.03301362, 0.03092113, 0.07978717, 0.03420616, 0.02481706,
# -0.03479896, 0.01136372, 0.02234516, -0.02502409, 0.02136666,
# -0.01978885, 0.01426617, 0.0336206 , 0.00164481, 0.05059334,
# -0.05926166, 0.01984084, -0.09437344, 0.00440842, -0.06748072,
# 0.04547653, 0.04531173, 0.02839815, 0.01182417, 0.01309258,
# 0.03345039, -0.0050239 , 0.00861029, -0.05667242, 0.01330826,
# 0.02976079, 0.03610174, 0.0056701 , -0.06830816, 0.07686577,
# 0.00055387, -0.07641901, 0.00479465, 0.0435739 , 0.00137714,
# 0.054296 , 0.02192332, 0.03526516, 0.03261713, -0.01711978,
# 0.05103486, 0.004091 , -0.04905723, 0.01632674, -0.04963868,
# 0.04549154, 0.05771144, 0.01438812, -0.08240737, -0.06134431,
# -0.03986251, 0.03224541, 0.00400033, -0.05963603, 0.02552675,
# 0.04327708, 0.00562372, 0.03411512, -0.11604068, 0.00232808,
# 0.02742139, 0.01270449, 0.02279026, -0.06613689, 0.00456405,
# 0.00770958, 0.01518244, -0.03575909, 0.05028789, 0.03181706,
# -0.02811741, 0.02930666, 0.02258663, -0.06209057, 0.01053006,
# 0.01761598, 0.02432001, -0.0141328 , 0.03561908, 0.03293756,
# 0.04713007, 0.02588944, 0.0185135 , 0.00973485, -0.09059389,
# -0.06192823, -0.0214373 , 0.02466835, -0.05554106, 0.03954491,
# -0.03995424, 0.03540933, -0.05664941, 0.00685676, 0.02727092,
# -0.06838219, 0.04708575, 0.06957678, -0.0574585 , -0.08372921,
# -0.06601643, -0.02683325, 0.02862075, 0.06086589, -0.05693608,
# 0.02700268, 0.03062632, -0.0449043 , -0.03139404, 0.01131762,
# 0.018201 , -0.05808553, 0.02667459, 0.02892675, -0.05436037,
# 0.02801878, 0.04307706, 0.0013432 , -0.06306062, -0.04901182,
# -0.05647411, 0.0226799 , -0.06727529, 0.10902219, 0.03856311,
# -0.04592182, -0.00500258, 0.00186311, -0.05330509, 0.05230814,
# -0.10676292, 0.01777823, 0.01183014, 0.05641989, 0.04702727,
# 0.00042184, -0.08117392, -0.00340278, 0.01055175, 0.02158776,
# 0.00645116, 0.05420727, -0.05439884, 0.02988858, -0.0155564 ,
# -0.00187941, 0.04348213, 0.02176837, 0.04492295, 0.05255244,
# -0.09009198, -0.12785755, 0.0270214 , 0.01281871, 0.03488814,
# 0.01032432, 0.03737413, -0.08046219, 0.03366841, 0.04788679,
# 0.02247225, 0.02758352, -0.05623886, 0.03350434, -0.03293617,
# 0.00674522, 0.02637025, -0.06836043, -0.03543041, 0.04120062,
# 0.04781871, -0.0528533 , 0.05126699, 0.01553862, 0.03617714,
# 0.0096033 , 0.01169565, -0.06753531, -0.05359954, -0.07725069,
# -0.0690423 , 0.00608264, 0.03367587, -0.01095485, 0.02317013,
# -0.03748006, -0.0396716 , -0.07376339, -0.15511133, -0.02377705,
# -0.0733289 , -0.02155393, 0.03737415, -0.00152944, -0.05182485,
# 0.0202742 , 0.04189592, 0.05077221, 0.02522502, -0.04805434,
# -0.03909 , -0.01301163, -0.02148154, 0.02039445, 0.02322994,
# 0.01821164, 0.03498985, 0.00654902, 0.00980544, -0.06337985,
# 0.00158023, 0.01253585, 0.05249537, 0.00056358, -0.03539167,
# 0.04533946, 0.02057356, 0.00598625, 0.00438659, -0.00444954,
# 0.04846435, 0.02074119, 0.00665891, 0.0347768 , -0.00355295,
# -0.00983169, 0.01239159, -0.06600927, -0.06987962, 0.04164324,
# -0.00596055, 0.01529142, 0.04804419, 0.04481226, -0.06791846,
# 0.04703787, -0.01586268, -0.06848218, 0.03964271, 0.03287267,
# -0.00166699, 0.05269769, 0.02563164, 0.00356486, -0.04681876,
# -0.05530458, 0.00568418, -0.00581932, 0.0229376 , 0.06235321,
# -0.03780747, -0.04042193, 0.01800834, 0.02682916, 0.05686411,
# 0.03996282, -0.05146077, 0.0312879 , -0.03907526, -0.01055358,
# -0.05896859, 0.02441409, -0.03880213, 0.03941878, 0.02211095,
# 0.00688374, -0.05528738, -0.01232414, -0.06249457, -0.07299529,
# 0.00938593, 0.05738097, -0.06533916, 0.03651554, 0.06204324,
# -0.01556815, -0.04757515, 0.0451969 , 0.03502326, -0.01376748,
# 0.02549847, -0.06043207]]).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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