Spaces:
Running
Running
File size: 5,688 Bytes
7f1afcd daad6da 7f1afcd a4107b1 297e244 a4107b1 297e244 a4107b1 297e244 a4107b1 297e244 a4107b1 0f191f9 daad6da 0f191f9 a4107b1 daad6da 0f191f9 daad6da 0f191f9 daad6da 297e244 daad6da d15da79 a4107b1 d15da79 a4107b1 daad6da d15da79 daad6da d15da79 daad6da d15da79 daad6da d15da79 daad6da a4107b1 7f1afcd a4107b1 |
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 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 |
import gradio as gr
from zeroshot import (
process,
WORD_SCORE_DEFAULT_IF_LM,
WORD_SCORE_DEFAULT_IF_NOLM,
LM_SCORE_DEFAULT,
)
with gr.Blocks(css="style.css") as demo:
gr.Markdown(
"<p align='center' style='font-size: 20px;'>MMS Zero-shot ASR Demo. See our arXiV <a href='https://arxiv.org/'>paper</a> for model details.</p>"
)
gr.HTML(
"""<center>The demo works on input audio in any language, as long as you provide a list of words or sentences for that language and an optional n-gram language model (even a simple 1-gram model will work!) to help with accuracy.<br>We recommend having a minimum of 5000 distinct words in the textfile to acheive a good performance.</center>"""
)
with gr.Row():
with gr.Column():
audio = gr.Audio(label="Audio Input\n(use microphone or upload a file)")
with gr.Row():
words_file = gr.File(label="Text Data")
lm_file = gr.File(label="Language Model\n(optional)")
with gr.Accordion("Advanced Settings", open=False):
gr.Markdown(
"The following parameters are used for beam-search decoding. Use the default values if you are not sure."
)
with gr.Row():
with gr.Column():
wscore_usedefault = gr.Checkbox(
label="Use Default Word Insertion Score", value=True
)
wscore = gr.Slider(
minimum=-10.0,
maximum=10.0,
value=WORD_SCORE_DEFAULT_IF_NOLM,
step=0.1,
interactive=False,
label="Word Insertion Score",
)
with gr.Column():
lmscore_usedefault = gr.Checkbox(
label="Use Default Language Model Score", value=True
)
lmscore = gr.Slider(
minimum=-10.0,
maximum=10.0,
value=0,
step=0.1,
interactive=False,
label="Language Model Score",
)
btn = gr.Button("Submit", elem_id="submit")
@gr.on(
inputs=[wscore_usedefault, lmscore_usedefault, lm_file],
outputs=[wscore, lmscore],
)
def update_slider(ws, ls, lm):
ws_slider = gr.Slider(
minimum=-10.0,
maximum=10.0,
value=LM_SCORE_DEFAULT if lm is not None else 0,
step=0.1,
interactive=not ws,
label="Word Insertion Score",
)
ls_slider = gr.Slider(
minimum=-10.0,
maximum=10.0,
value=WORD_SCORE_DEFAULT_IF_NOLM
if lm is None
else WORD_SCORE_DEFAULT_IF_LM,
step=0.1,
interactive=not ls,
label="Language Model Score",
)
return ws_slider, ls_slider
with gr.Column():
text = gr.Textbox(label="Transcript")
with gr.Accordion("Logs", open=False):
logs = gr.Textbox(show_label=False)
# hack
reference = gr.Textbox(label="Reference Transcript", visible=False)
btn.click(
process,
inputs=[
audio,
words_file,
lm_file,
wscore,
lmscore,
wscore_usedefault,
lmscore_usedefault,
reference
],
outputs=[text, logs],
)
# Examples
gr.Examples(
examples=[
# ["upload/english/english.mp3", "upload/english/c4_25k_sentences.txt"],
["upload/english/english.mp3", "upload/english/c4_10k_sentences.txt", " This is going to look at the code that we have in our configuration that we've already exported and compare it to our database, and we want to import"],
["upload/english/english.mp3", "upload/english/c4_5k_sentences.txt", " This is going to look at the code that we have in our configuration that we've already exported and compare it to our database, and we want to import"],
["upload/english/english.mp3", "upload/english/cv8_top10k_words.txt", " This is going to look at the code that we have in our configuration that we've already exported and compare it to our database, and we want to import"],
],
inputs=[audio, words_file, reference],
label="English",
)
gr.Examples(
examples=[
# ["upload/english/english.mp3", "upload/english/c4_25k_sentences.txt"],
["upload/ligurian/ligurian_1.mp3", "upload/ligurian/zenamt_10k_sentences.txt", "I mæ colleghi m’an domandou d’aggiuttâli à fâ unna preuva co-o zeneise pe vedde s’o fonçioña."],
["upload/ligurian/ligurian_2.mp3", "upload/ligurian/zenamt_10k_sentences.txt", "Staseia vaggo à çenâ con mæ moggê e doî amixi che de chì à quarche settemaña faian stramuo feua stato."],
["upload/ligurian/ligurian_3.mp3", "upload/ligurian/zenamt_5k_sentences.txt", "Pe inandiâ o pesto ghe veu o baxaicò, i pigneu, l’euio, o formaggio, l’aggio e a sâ."],
],
inputs=[audio, words_file, reference],
label="Ligurian",
)
demo.launch()
|