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| import torch | |
| import gradio as gr | |
| from transformers import pipeline | |
| import tempfile | |
| from neon_tts_plugin_coqui import CoquiTTS | |
| from datetime import datetime | |
| import time | |
| import psutil | |
| from mtranslate import translate | |
| from gpuinfo import GPUInfo | |
| MODEL_NAME = "cahya/whisper-medium-id" # this always needs to stay in line 8 :D sorry for the hackiness | |
| whisper_models = { | |
| "Indonesian Whisper Medium": { | |
| "name": "cahya/whisper-medium-id", | |
| "pipe": None, | |
| } | |
| } | |
| lang = "id" | |
| title = "Indonesian Whisperer" | |
| description = "Cross Language Speech to Speech (Indonesian/English to 25 other languages) using OpenAI Whisper and Coqui TTS" | |
| info = "This application uses [Indonesian Whisperer Medium](https://huggingface.co/cahya/whisper-medium-id) model" | |
| badge = "https://img.shields.io/badge/Powered%20by-Indonesian%20Whisperer-red" | |
| visitors = "https://visitor-badge.glitch.me/badge?page_id=cahya-hf-indonesian-whisperer" | |
| languages = { | |
| 'English': 'en', | |
| 'German': 'de', | |
| 'Spanish': 'es', | |
| 'French': 'fr', | |
| 'Portuguese': 'pt', | |
| 'Polish': 'pl', | |
| 'Dutch': 'nl', | |
| 'Swedish': 'sv', | |
| 'Italian': 'it', | |
| 'Finnish': 'fi', | |
| 'Ukrainian': 'uk', | |
| 'Greek': 'el', | |
| 'Czech': 'cs', | |
| 'Romanian': 'ro', | |
| 'Danish': 'da', | |
| 'Hungarian': 'hu', | |
| 'Croatian': 'hr', | |
| 'Bulgarian': 'bg', | |
| 'Lithuanian': 'lt', | |
| 'Slovak': 'sk', | |
| 'Latvian': 'lv', | |
| 'Slovenian': 'sl', | |
| 'Estonian': 'et', | |
| 'Maltese': 'mt' | |
| } | |
| device = 0 if torch.cuda.is_available() else "cpu" | |
| for model in whisper_models: | |
| whisper_models[model]["pipe"] = pipeline( | |
| task="automatic-speech-recognition", | |
| model=whisper_models[model]["name"], | |
| chunk_length_s=30, | |
| device=device, | |
| ) | |
| whisper_models[model]["pipe"].model.config.forced_decoder_ids = \ | |
| whisper_models[model]["pipe"].tokenizer.get_decoder_prompt_ids(language=lang, task="transcribe") | |
| def transcribe(pipe, microphone, file_upload): | |
| warn_output = "" | |
| if (microphone is not None) and (file_upload is not None): | |
| warn_output = ( | |
| "WARNING: You've uploaded an audio file and used the microphone. " | |
| "The recorded file from the microphone will be used and the uploaded audio will be discarded.\n" | |
| ) | |
| elif (microphone is None) and (file_upload is None): | |
| return "ERROR: You have to either use the microphone or upload an audio file" | |
| file = microphone if microphone is not None else file_upload | |
| text = pipe(file)["text"] | |
| return warn_output + text | |
| LANGUAGES = list(CoquiTTS.langs.keys()) | |
| default_lang = "en" | |
| coquiTTS = CoquiTTS() | |
| def process(language: str, model: str, audio_microphone: str, audio_file: str): | |
| language = languages[language] | |
| pipe = whisper_models[model]["pipe"] | |
| time_start = time.time() | |
| print(f"### {datetime.now()} TTS", language, audio_file) | |
| transcription = transcribe(pipe, audio_microphone, audio_file) | |
| print(f"### {datetime.now()} transcribed:", transcription) | |
| translation = translate(transcription, language, "id") | |
| # return output | |
| with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp: | |
| coquiTTS.get_tts(translation, fp, speaker={"language": language}) | |
| time_end = time.time() | |
| time_diff = time_end - time_start | |
| memory = psutil.virtual_memory() | |
| gpu_utilization, gpu_memory = GPUInfo.gpu_usage() | |
| gpu_utilization = gpu_utilization[0] if len(gpu_utilization) > 0 else 0 | |
| gpu_memory = gpu_memory[0] if len(gpu_memory) > 0 else 0 | |
| system_info = f""" | |
| *Memory: {memory.total / (1024 * 1024 * 1024):.2f}GB, used: {memory.percent}%, available: {memory.available / (1024 * 1024 * 1024):.2f}GB.* | |
| *Processing time: {time_diff:.5} seconds.* | |
| *GPU Utilization: {gpu_utilization}%, GPU Memory: {gpu_memory}MiB.* | |
| """ | |
| print(f"### {datetime.now()} fp.name:", fp.name) | |
| return transcription, translation, fp.name, system_info | |
| with gr.Blocks() as blocks: | |
| gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>" | |
| + title | |
| + "</h1>") | |
| gr.Markdown(description) | |
| with gr.Row(): # equal_height=False | |
| with gr.Column(): # variant="panel" | |
| audio_microphone = gr.Audio(label="Microphone", source="microphone", type="filepath", optional=True) | |
| audio_upload = gr.Audio(label="Upload", source="upload", type="filepath", optional=True) | |
| language = gr.Dropdown([lang for lang in languages.keys()], label="Target Language", value="English") | |
| model = gr.Dropdown([model for model in whisper_models.keys()], | |
| label="Whisper Model", value="Indonesian Whisper Medium") | |
| with gr.Row(): # mobile_collapse=False | |
| submit = gr.Button("Submit", variant="primary") | |
| examples = gr.Examples(examples=["data/Jokowi - 2022.mp3", "data/Soekarno - 1963.mp3", "data/JFK.mp3"], | |
| label="Examples", inputs=[audio_upload]) | |
| with gr.Column(): | |
| text_source = gr.Textbox(label="Source Language") | |
| text_target = gr.Textbox(label="Target Language") | |
| audio = gr.Audio(label="Target Audio", interactive=False) | |
| memory = psutil.virtual_memory() | |
| system_info = gr.Markdown(f"*Memory: {memory.total / (1024 * 1024 * 1024):.2f}GB, used: {memory.percent}%, available: {memory.available / (1024 * 1024 * 1024):.2f}GB*") | |
| gr.Markdown(info) | |
| gr.Markdown("<center>" | |
| + f'<a href="https://github.com/cahya-wirawan/indonesian-whisperer"><img src={badge} alt="visitors badge"/></a>' | |
| + f'<img src={visitors} alt="visitors badge"/>' | |
| + "</center>") | |
| # actions | |
| submit.click( | |
| process, | |
| [language, model, audio_microphone, audio_upload], | |
| [text_source, text_target, audio, system_info], | |
| ) | |
| blocks.launch(server_port=7870) | |