Spaces:
Build error
Build error
| import gradio as gr | |
| import librosa | |
| from transformers import AutoFeatureExtractor, AutoTokenizer, SpeechEncoderDecoderModel | |
| model_name = "facebook/wav2vec2-xls-r-1b-en-to-15", | |
| feature_extractor = AutoFeatureExtractor.from_pretrained(model_name, use_auth_token="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") | |
| tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token="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", use_fast=False) | |
| model = SpeechEncoderDecoderModel.from_pretrained(model_name, use_auth_token="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") | |
| def process_audio_file(file): | |
| data, sr = librosa.load(file) | |
| if sr != 16000: | |
| data = librosa.resample(data, sr, 16000) | |
| print(data.shape) | |
| input_values = feature_extractor(data, return_tensors="pt").input_values | |
| return input_values | |
| def transcribe(file, target_language): | |
| target_code = target_language.split("(")[-1].split(")")[0] | |
| forced_bos_token_id = MAPPING[target_code] | |
| input_values = process_audio_file(file) | |
| sequences = model.generate(input_values, forced_bos_token_id=forced_bos_token_id) | |
| transcription = tokenizer.batch_decode(sequences, skip_special_tokens=True) | |
| return transcription[0] | |
| target_language = [ | |
| "English (en)", | |
| "German (de)", | |
| "Turkish (tr)", | |
| "Persian (fa)", | |
| "Swedish (sv)", | |
| "Mongolian (mn)", | |
| "Chinese (zh)", | |
| "Welsh (cy)", | |
| "Catalan (ca)", | |
| "Slovenian (sl)", | |
| "Estonian (et)", | |
| "Indonesian (id)", | |
| "Arabic (ar)", | |
| "Tamil (ta)", | |
| "Latvian (lv)", | |
| "Japanese (ja)", | |
| ] | |
| MAPPING = { | |
| "en": 250004, | |
| "de": 250003, | |
| "tr": 250023, | |
| "fa": 250029, | |
| "sv": 250042, | |
| "mn": 250037, | |
| "zh": 250025, | |
| "cy": 250007, | |
| "ca": 250005, | |
| "sl": 250052, | |
| "et": 250006, | |
| "id": 250032, | |
| "ar": 250001, | |
| "ta": 250044, | |
| "lv": 250017, | |
| "ja": 250012, | |
| } | |
| iface = gr.Interface( | |
| fn=transcribe, | |
| inputs=[ | |
| gr.inputs.Audio(source="microphone", type='filepath'), | |
| gr.inputs.Dropdown(target_language), | |
| ], | |
| outputs="text", | |
| layout="horizontal", | |
| theme="huggingface", | |
| title="XLS-R 1B EN-to-15 Speech Translation", | |
| description="A simple interface to translate from spoken English to 15 written languages.", | |
| ) | |
| iface.launch() | |