Hugging Face's logo

Spaces:
facebook
/
XLS-R-1B-EN-15
Build error

App Files Community
XLS-R-1B-EN-15
File size: 2,291 Bytes 
8bdd0da
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
 
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()