File size: 1,831 Bytes
911ea43 090e095 ccea760 a9861ea 65900fb 092f19b 911ea43 092f19b 911ea43 369ac5b ccea760 911ea43 092f19b ccea760 911ea43 a9861ea 369ac5b cf7e255 a9861ea 090e095 ae08875 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 |
from transformers import SpeechT5Processor, SpeechT5ForTextToSpeech, SpeechT5HifiGan
from datasets import load_dataset
import torch
import soundfile as sf
from datasets import load_dataset
from transformers import pipeline
import gradio as gr
import tempfile
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
speech = pipeline("text-to-speech", model="microsoft/speecht5_tts")
# code from the Model card
processor = SpeechT5Processor.from_pretrained("microsoft/speecht5_tts")
model = SpeechT5ForTextToSpeech.from_pretrained("microsoft/speecht5_tts")
vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan")
speaker_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
speaker_embeddings = torch.tensor(speaker_dataset[0]["xvector"]).unsqueeze(0)
def summarize_text_and_speak(prompt):
summary = summarizer(prompt, max_length=150, min_length=30, do_sample=False)
summary_text = summary[0]['summary_text']
#inputs = processor(text="Hello, my dog is cute.", return_tensors="pt")
inputs = processor(text=summary_text, return_tensors="pt")
#speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder)
speech_audio = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder)
#sf.write("speech.wav", speech.numpy(), samplerate=16000)
with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_file:
sf.write(tmp_file.name, speech_audio.numpy(), samplerate=16000)
audio_path = tmp_file.name
return summary_text, audio_path
interface = gr.Interface(
fn=summarize_text_and_speak,
inputs=gr.Textbox(lines=10, label="Input text"),
outputs=[gr.Textbox(label="Summary"), gr.Audio(label="Audio")]
)
interface.launch(share=True)
|