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README.md

@@ -1,12 +1,6 @@
 ---
-title: Text To Speech Italian
-emoji: 🐢
-colorFrom: gray
-colorTo: green
-sdk: gradio
-sdk_version: 3.36.1
+title: text-to-speech-italian
 app_file: app.py
-pinned: false
+sdk: gradio
+sdk_version: 3.36.0
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import torch
+from datasets import load_dataset
+from transformers import pipeline, SpeechT5HifiGan, SpeechT5ForTextToSpeech
+
+model_id = "Sandiago21/speecht5_finetuned_voxpopuli_it"  # update with your model id
+# pipe = pipeline("automatic-speech-recognition", model=model_id)
+model = SpeechT5ForTextToSpeech.from_pretrained(model_id)
+vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan").cuda()
+embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
+speaker_embeddings = torch.tensor(embeddings_dataset[7440]["xvector"]).unsqueeze(0)
+
+def synthesize_speech(text):
+    inputs = processor(text=text, return_tensors="pt")
+
+    speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder)
+    
+    return gr.Audio.update(value=(16000, speech.cpu().numpy()))
+
+syntesize_speech_gradio = gr.Interface(
+    synthesize_speech,
+    inputs = gr.Textbox(label="Text", placeholder="Type something here..."),
+    outputs=gr.Audio(),
+#     title="Hot Dog? Or Not?",
+).launch()
+

requirements.txt

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+transformers
+torch
+datasets
+