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import spaces | |
import gradio as gr | |
import numpy as np | |
import torch | |
from datasets import load_dataset | |
from transformers import SpeechT5ForTextToSpeech, SpeechT5HifiGan, SpeechT5Processor, pipeline | |
device = "cuda:0" if torch.cuda.is_available() else "cpu" | |
# load speech translation checkpoint | |
asr_pipe = pipeline("automatic-speech-recognition", model="oyemade/w2v-bert-2.0-yoruba-colab-CV16.1", device=device) | |
# load text-to-speech checkpoint and speaker embeddings | |
processor = SpeechT5Processor.from_pretrained("microsoft/speecht5_tts") | |
model = SpeechT5ForTextToSpeech.from_pretrained("microsoft/speecht5_tts").to(device) | |
vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan").to(device) | |
embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation", revision="refs/convert/parquet") | |
speaker_embeddings = torch.tensor(embeddings_dataset[7306]["xvector"]).unsqueeze(0) | |
translation_model = pipeline("translation", "facebook/nllb-200-distilled-600M", src_lang="yor_Latn", tgt_lang="eng_Latn", device=device) | |
def translate(audio): | |
text = asr_pipe(audio)["text"] | |
# print(text) | |
translation = translation_model(text) | |
# print(translation[0]['translation_text']) | |
return translation[0]['translation_text'] | |
def synthesise(text): | |
inputs = processor(text=text, return_tensors="pt") | |
speech = model.generate_speech(inputs["input_ids"].to(device), speaker_embeddings.to(device), vocoder=vocoder) | |
return speech.cpu() | |
def speech_to_speech_translation(audio): | |
# print(model) | |
translated_text = translate(audio) | |
synthesised_speech = synthesise(translated_text) | |
synthesised_speech = (synthesised_speech.numpy() * 32767).astype(np.int16) | |
return 16000, synthesised_speech | |
iface = gr.Interface( | |
speech_to_speech_translation, | |
gr.Audio(sources=["microphone", "upload"], type="filepath"), | |
gr.Audio(label="Generated Speech", type="numpy"), | |
title="Neoform AI: Yoruba Speech to English Speech", | |
description="Demo for Yoruba speech translated to English Speech. NOTE: If you get an ERROR after pressing submit, give the audio some secs to load then try again.", | |
) | |
iface.launch() |