Create tts_transformers_stream.py

tts_transformers_stream.py

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+import streamlit as st
+from transformers import SpeechT5Processor, SpeechT5ForTextToSpeech, SpeechT5HifiGan
+from datasets import load_dataset
+import torch
+import soundfile as sf
+import random
+import time
+
+st.title('Multiply TTS Generator')
+
+text = st.text_input(
+    label="write your word or sentence",
+    value="Hi,duino"
+)
+
+num_random_voices = st.number_input(
+    label="Enter the number of random voices",
+    min_value=1,
+    value=1,
+    step=1
+)
+
+output_filename = ""
+
+def generate_speech():
+    global output_filename
+
+    processor = SpeechT5Processor.from_pretrained("microsoft/speecht5_tts")
+    model = SpeechT5ForTextToSpeech.from_pretrained("microsoft/speecht5_tts")
+    vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan")
+    inputs = processor(text=text, return_tensors="pt")
+
+    embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
+    total_voices = len(embeddings_dataset)
+
+    random_voices = random.sample(range(total_voices), num_random_voices)
+
+    combined_speech = []
+    for index, voice_index in enumerate(random_voices):
+        speaker_embeddings = torch.tensor(embeddings_dataset[voice_index]["xvector"]).unsqueeze(0)
+        speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder)
+        combined_speech.extend(speech.numpy())
+
+        if index != len(random_voices) - 1:
+            # Add a pause of 2 seconds between voices
+            pause_samples = int(16000 * 2)  # 2 seconds at 16kHz sample rate
+            pause = torch.zeros(pause_samples)
+            combined_speech.extend(pause)
+
+    output_filename = "_".join(text.split()) + "_speech.wav"
+    sf.write(output_filename, combined_speech, samplerate=16000)
+
+if st.button("Generate"):
+    generate_speech()
+    audio_file = open(output_filename, 'rb')
+    audio_bytes = audio_file.read()
+    st.audio(audio_bytes, format="audio/wav")
+    st.write("Speech generated and saved as: " + output_filename)