Spaces:
Running
Running
| import gradio as gr | |
| from aip_trainer import app_logger | |
| from aip_trainer.lambdas import lambdaSpeechToScore, lambdaTTS | |
| js = """ | |
| function updateCssText(text, letters) { | |
| let wordsArr = text.split(" ") | |
| let lettersWordsArr = letters.split(" ") | |
| let speechOutputContainer = document.querySelector('#speech-output'); | |
| speechOutputContainer.textContent = "" | |
| for (let idx in wordsArr) { | |
| let word = wordsArr[idx] | |
| let letterIsCorrect = lettersWordsArr[idx] | |
| for (let idx1 in word) { | |
| let letterCorrect = letterIsCorrect[idx1] == "1" | |
| let containerLetter = document.createElement("span") | |
| containerLetter.style.color = letterCorrect ? 'green' : "red" | |
| containerLetter.innerText = word[idx1]; | |
| speechOutputContainer.appendChild(containerLetter) | |
| } | |
| let containerSpace = document.createElement("span") | |
| containerSpace.textContent = " " | |
| speechOutputContainer.appendChild(containerSpace) | |
| } | |
| } | |
| """ | |
| with gr.Blocks() as gradio_app: | |
| app_logger.info("start gradio app building...") | |
| gr.Markdown( | |
| """ | |
| # AI Pronunciation Trainer | |
| See [my fork](https://github.com/trincadev/ai-pronunciation-trainer) of [AI Pronunciation Trainer](https://github.com/Thiagohgl/ai-pronunciation-trainer) repositroy | |
| for more details. | |
| """ | |
| ) | |
| with gr.Row(): | |
| with gr.Column(scale=4, min_width=300): | |
| with gr.Row(): | |
| with gr.Column(scale=1, min_width=50): | |
| language = gr.Radio(["de", "en"], label="Language", value="en") | |
| with gr.Column(scale=7, min_width=300): | |
| learner_transcription = gr.Textbox( | |
| lines=3, | |
| label="Learner Transcription", | |
| value="Hi there, how are you?", | |
| ) | |
| with gr.Row(): | |
| learner_recording = gr.Audio( | |
| label="Learner Recording", | |
| sources=["microphone", "upload"], | |
| type="filepath", | |
| ) | |
| with gr.Row(): | |
| tts = gr.Audio(label="tts") | |
| btn = gr.Button(value="TTS") | |
| btn.click( | |
| fn=lambdaTTS.get_tts, | |
| inputs=[learner_transcription, language], | |
| outputs=tts, | |
| ) | |
| with gr.Column(scale=3, min_width=300): | |
| transcripted_text = gr.Textbox( | |
| lines=2, placeholder=None, label="Transcripted text", visible=False | |
| ) | |
| letter_correctness = gr.Textbox( | |
| lines=1, | |
| placeholder=None, | |
| label="Letters correctness", | |
| visible=False, | |
| ) | |
| pronunciation_accuracy = gr.Textbox( | |
| lines=1, placeholder=None, label="Pronunciation accuracy %" | |
| ) | |
| recording_ipa = gr.Textbox( | |
| lines=1, placeholder=None, label="Learner phonetic transcription" | |
| ) | |
| ideal_ipa = gr.Textbox( | |
| lines=1, placeholder=None, label="Ideal phonetic transcription" | |
| ) | |
| res = gr.Textbox(lines=1, placeholder=None, label="RES", visible=False) | |
| html_output = gr.HTML( | |
| label="Speech accuracy output", | |
| elem_id="speech-output", | |
| show_label=True, | |
| visible=True, | |
| render=True, | |
| value=" - ", | |
| elem_classes="speech-output", | |
| ) | |
| btn = gr.Button(value="Recognize speech accuracy") | |
| # real_transcripts, is_letter_correct_all_words, pronunciation_accuracy, result['recording_ipa'], real_transcripts_ipa, res | |
| btn.click( | |
| lambdaSpeechToScore.get_speech_to_score_tuple, | |
| inputs=[learner_transcription, learner_recording, language], | |
| outputs=[ | |
| transcripted_text, | |
| letter_correctness, | |
| pronunciation_accuracy, | |
| recording_ipa, | |
| ideal_ipa, | |
| res, | |
| ], | |
| ) | |
| html_output.change( | |
| None, | |
| inputs=[transcripted_text, letter_correctness], | |
| outputs=[html_output], | |
| js=js, | |
| ) | |
| if __name__ == "__main__": | |
| gradio_app.launch() |