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README.md

@@ -1,12 +1,6 @@
 ---
-title: Text To Speech Spanish
-emoji: 🐢
-colorFrom: green
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.36.1
+title: text-to-speech-spanish
 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

@@ -0,0 +1,43 @@
+import gradio as gr
+import torch
+from datasets import load_dataset
+from transformers import pipeline, SpeechT5Processor, SpeechT5HifiGan, SpeechT5ForTextToSpeech
+
+model_id = "Sandiago21/speecht5_finetuned_voxpopuli_spanish"  # 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")
+embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
+speaker_embeddings = torch.tensor(embeddings_dataset[7440]["xvector"]).unsqueeze(0)
+
+checkpoint = "microsoft/speecht5_tts"
+processor = SpeechT5Processor.from_pretrained(checkpoint)
+
+replacements = [
+    ("á", "a"),
+    ("í", "i"),
+    ("ñ", "n"),
+    ("ó", "o"),
+    ("ú", "u"),
+    ("ü", "u"),
+]
+
+def cleanup_text(text):
+    for src, dst in replacements:
+        text = text.replace(src, dst)
+    return text
+
+def synthesize_speech(text):
+    text = cleanup_text(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(),
+).launch()
+

requirements.txt

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+transformers
+torch
+datasets
+torchaudio
+sentencepiece==0.1.99
+