Update requirements.txt, TTS.py

TTS.py

+import torch
+from transformers import pipeline
+import soundfile as sf
+from datasets import load_dataset
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+class TextToSpeech():
+    AnswerText = None
+    AnswerAudio = None
+
+    def funcTextToSpeech(self, input):
+        synthesiser = pipeline("text-to-speech", "microsoft/speecht5_tts",device=device)
+
+        embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
+        speaker_embedding = torch.tensor(embeddings_dataset[7306]["xvector"]).unsqueeze(0)
+        # You can replace this embedding with your own as well.
+
+        speech = synthesiser(input,
+                                forward_params={"speaker_embeddings": speaker_embedding})
+
+
+        path_output = "AudioAnswer.wav"
+        sf.write(path_output, speech["audio"], samplerate=speech["sampling_rate"])
+        return path_output
+
+    def run(self):
+        self.AnswerAudio = self.funcTextToSpeech(self.AnswerText)
+
+if __name__ == '__main__':
+    module = TextToSpeech()
+    module.AnswerText="Text as a string"
+    module.run()

requirements.txt

+torch
+transformers
+datasets
+soundfile