| import gradio as gr | |
| import torch | |
| from transformers import SpeechT5ForTextToSpeech, SpeechT5Processor, SpeechT5HifiGan | |
| import soundfile as sf | |
| model = SpeechT5ForTextToSpeech.from_pretrained("Beehzod/speecht5_finetuned_uz_customData2") | |
| processor = SpeechT5Processor.from_pretrained("Beehzod/speecht5_finetuned_uz_customData2") | |
| vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan") | |
| speaker_embeddings = torch.zeros((1, 512)) | |
| def text_to_speech(text): | |
| inputs = processor(text=text, return_tensors="pt") | |
| speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder) | |
| output_path = "output.wav" | |
| sf.write(output_path, speech.numpy(), 16000) | |
| return output_path | |
| interface = gr.Interface( | |
| fn=text_to_speech, | |
| inputs="text", | |
| outputs="audio", | |
| title="Uzbek Text-to-Speech Generator", | |
| description="Enter Uzbek text and generate speech using the finetuned SpeechT5 model." | |
| ) | |
| interface.launch() | |