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import gradio as gr
from transformers import pipeline
import time
from fairseq.checkpoint_utils import load_model_ensemble_and_task_from_hf_hub
from fairseq.models.text_to_speech.hub_interface import TTSHubInterface
import torch
from fairseq.utils import move_to_cuda
"""
Notes:
pip install sentencepiece
pip install phonemizer
install ffmpeg and add to path
Must install e-speak to path
solution
1.Download and install the Windows version of espeak: http://espeak.sourceforge.net/download.html
2. set PATH=%PATH%;"C:\Program Files (x86)\eSpeak\command_line"_
3. Install .msi from https://github.com/espeak-ng/espeak-ng/releases
4.Enter environment variable
1.PHONEMIZER_ESPEAK_LIBRARY="c:\Program Files\eSpeak NG\libespeak-ng.dll"
2.PHONEMIZER_ESPEAK_PATH =“c:\Program Files\eSpeak NG”
and Restart your Computer. Run the same command again from the Command Prompt (cmd.exe):
"""
asr = pipeline("automatic-speech-recognition",model="facebook/wav2vec2-base-960h" )
translation_pipeline = pipeline('translation_en_to_es',model = "Helsinki-NLP/opus-mt-en-es" ) #This model version is built for en- to -fr , less mistakes
models, cfg, task = load_model_ensemble_and_task_from_hf_hub(
"facebook/tts_transformer-es-css10",
arg_overrides={"vocoder": "hifigan", "fp16": False}
)
model = models[0]
model = model.to(torch.device("cuda:0")) if torch.cuda.is_available() else model
TTSHubInterface.update_cfg_with_data_cfg(cfg, task.data_cfg)
generator = task.build_generator(models, cfg)
def transcribe_translate(audio):
time.sleep(3)
text_en = asr(audio)["text"]
text_fr = translation_pipeline(text_en.lower()) # for some reason all audio converted to all caps and it translates differently???
text_fr = text_fr[0]['translation_text'] # good evening = bonsoir but GOOD EVENING = BONNES SÉANCES . WEIRD
sample = TTSHubInterface.get_model_input(task, text_fr)
sample = move_to_cuda(sample) if torch.cuda.is_available() else sample
wav, rate = TTSHubInterface.get_prediction(task, model, generator, sample)
wav = wav.to('cpu')
wav = wav.numpy()
print(wav.dtype)
return text_en,text_fr , (rate,wav)
gr.Interface(
fn=transcribe_translate,
inputs=[
gr.Audio(source="microphone", type="filepath")
],
outputs=[
gr.Textbox(label= "English Transcription"),
gr.Textbox(label= "Spanish Translation"),
gr.Audio(label = "Spanish Audio")
],
live=True).launch(share=True)
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