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| import gradio as gr | |
| #Get models | |
| #ASR model for input speech | |
| speech2text = gr.Interface.load("huggingface/facebook/wav2vec2-base-960h", | |
| inputs=gr.inputs.Audio(label="Record Audio File", type="file", source = "microphone")) | |
| #translates english to spanish text | |
| translator = gr.Interface.load("huggingface/Helsinki-NLP/opus-mt-en-es", | |
| outputs=gr.outputs.Textbox(label="English to Spanish Translated Text")) | |
| #TTS model for output speech | |
| text2speech = gr.Interface.load("huggingface/facebook/tts_transformer-es-css10", | |
| outputs=gr.outputs.Audio(label="English to Spanish Translated Audio"), | |
| allow_flagging="never") | |
| translate = gr.Series(speech2text, translator) #outputs Spanish text translation | |
| en2es = gr.Series(translate, text2speech) #outputs Spanish audio | |
| ui = gr.Parallel(translate, en2es) #allows transcription of Spanish audio | |
| #gradio interface | |
| ui.title = "English to Spanish Speech Translator" | |
| ui.description = """<center>A useful tool in translating English to Spanish audio. All pre-trained models are found in huggingface.</center>""" | |
| ui.examples = [['ljspeech.wav'],['ljspeech2.wav',]] | |
| ui.theme = "peach" | |
| ui.article = article=""<h2>Pre-trained model Information</h2> | |
| <h3>Automatic Speech Recognition</h3> | |
| <p style='text-align: justify'>The model used for the ASR part of this space is from | |
| <https://huggingface.co/facebook/wav2vec2-base-960h> which is pretrained and fine-tuned on <b>960 hours of | |
| Librispeech</b> on 16kHz sampled speech audio. This model has a <b>word error rate (WER)</b> of <b>8.6 percent on | |
| noisy speech</b> and <b>5.2 percent on clean speech</b> on the standard LibriSpeech benchmark. More information can be | |
| found on its website at <https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/> and | |
| original model is under <https://github.com/pytorch/fairseq/tree/main/examples/wav2vec>.</p> | |
| <h3>Text Translator</h3> | |
| <p style='text-align: justify'>The English to Spanish text translator pre-trained model is from <Helsinki-NLP/opus- | |
| mt-en-es> which is part of the <b>The Tatoeba Translation Challenge (v2021-08-07)</b> as seen from its github repo at | |
| <https://github.com/Helsinki-NLP/Tatoeba-Challenge>. This project aims to develop machine translation in real-world | |
| cases for many languages. </p> | |
| <h3>Text to Speech</h3> | |
| <p style='text-align: justify'> The TTS model used is from <https://huggingface.co/facebook/tts_transformer-es-css10>. | |
| This model uses the <b>Fairseq(-py)</b> sequence modeling toolkit for speech synthesis, in this case, specifically TTS | |
| for Spanish. More information can be seen on their git at <https://github.com/pytorch/fairseq>. </p> | |
| "" | |
| ui.launch(inbrowser=True) | |