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import gradio as gr | |
from transformers import pipeline | |
from espnet2.bin.tts_inference import Text2Speech | |
def generateTextAndAudio(inputText, numGen): | |
# --- Generating the Text --- | |
# With the provided text from user, generate more text up to `numGen` tokens/sub-words | |
textOutput = textGenerator(inputText, max_length = numGen) | |
# The output of the text generator is a list of dictionaries, grab the first dictionary | |
# then get the generated text from the dictionary using the `generated_text` key | |
genText = textOutput[0]['generated_text'] | |
print("Input Text:", inputText) | |
print("Generated Text:", genText) | |
# --- Generating the Audio --- | |
# With the newly generated text, generate some speech | |
audioOutput = audioGenerator(genText) | |
# Get the wav data | |
genAudio = audioOutput['wav'] | |
# Return two things | |
# 1) Generated Text | |
# 2) 24k sampling rate, and the Generated Audio (wav) as numpy (instead of tensor) | |
return genText, (24000, genAudio.numpy()) | |
# Main | |
textGenerator = pipeline('text-generation', model = 'gpt2') | |
audioGenerator = Text2Speech.from_pretrained("espnet/kan-bayashi_ljspeech_joint_finetune_conformer_fastspeech2_hifigan") | |
input1_textbox = gr.Textbox(label="Input text") | |
input2_slider = gr.Slider(minimum=1, maximum=100, step=1, default=30, label="Number of words to generate") | |
output1_textbox = gr.Textbox(label = "Generated Text") | |
output2_Audio = gr.Audio(label = "Generated Audio") | |
title = "Generate Text and it's Audio!" | |
description = "Provide the text, and how many subwords to generate" | |
examples = [ | |
["I won a", 50], | |
["My name is", 30], | |
["I have", 60] | |
] | |
article = "<p style='text-align: center'><img src='https://visitor-badge.glitch.me/badge?page_id=epoching_glide_inpaint' alt='visitor badge'></p>" | |
iface = gr.Interface(fn=generateTextAndAudio, | |
inputs=[input1_textbox, input2_slider], | |
outputs=[output1_textbox, output2_Audio], | |
title=title, | |
description=description, | |
examples=examples | |
article=article).launch(debug = True) |