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@@ -79,18 +79,24 @@ installs
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  inference
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  ```python
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-
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  from transformers import pipeline
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  from datasets import load_dataset
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  import soundfile as sf
 
 
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  synthesiser = pipeline("text-to-speech", "umarigan/speecht5_tts_tr_v1.0")
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- embeddings_dataset = load_dataset("umarigan/turkish_voice_dataset_embedded", split="train[:500]", stream = True)
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  speaker_embedding = torch.tensor(embeddings_dataset[736]["speaker_embeddings"]).unsqueeze(0)
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- # You can replace this embedding with your own as well.
 
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  speech = synthesiser("Bir berber bir berbere gel beraber bir berber kuralım demiş", forward_params={"speaker_embeddings": speaker_embedding})
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  sf.write("speech.wav", speech["audio"], samplerate=speech["sampling_rate"])
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  ```
 
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  inference
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  ```python
 
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  from transformers import pipeline
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  from datasets import load_dataset
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  import soundfile as sf
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+ import torch
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+ from IPython.display import Audio
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  synthesiser = pipeline("text-to-speech", "umarigan/speecht5_tts_tr_v1.0")
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+ embeddings_dataset = load_dataset("umarigan/turkish_voice_dataset_embedded", split="train")
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  speaker_embedding = torch.tensor(embeddings_dataset[736]["speaker_embeddings"]).unsqueeze(0)
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+
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+ # Synthesize speech using the embedding
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  speech = synthesiser("Bir berber bir berbere gel beraber bir berber kuralım demiş", forward_params={"speaker_embeddings": speaker_embedding})
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+ # Save the generated audio to a file
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  sf.write("speech.wav", speech["audio"], samplerate=speech["sampling_rate"])
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+ # Play the audio in the notebook
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+ Audio("speech.wav")
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+
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  ```