Spaces:
Running
Running
File size: 6,339 Bytes
7f1afcd daad6da 7f1afcd a4107b1 297e244 a4107b1 297e244 a4107b1 297e244 a4107b1 297e244 a4107b1 0f191f9 1be831a 0f191f9 daad6da 0f191f9 1be831a 0f191f9 6f27821 a4107b1 daad6da 6f27821 daad6da 6f27821 0f191f9 6f27821 0f191f9 daad6da 6f27821 daad6da 0f191f9 daad6da 297e244 daad6da 78e8beb d15da79 a4107b1 6f27821 78e8beb a4107b1 daad6da 78e8beb 6f27821 78e8beb daad6da d15da79 daad6da 78e8beb 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 |
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_LM,
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=LM_SCORE_DEFAULT,
step=0.1,
interactive=False,
label="Language Model Score",
)
with gr.Column():
autolm = gr.Checkbox(
label="Automatically create Unigram LM from text data", value=True
)
btn = gr.Button("Submit", elem_id="submit")
@gr.on(
inputs=[wscore_usedefault, lmscore_usedefault, lm_file, autolm],
outputs=[wscore, lmscore],
)
def update_slider(ws, ls, lm, alm):
ws_slider = gr.Slider(
minimum=-10.0,
maximum=10.0,
value=LM_SCORE_DEFAULT if (lm is not None or alm) 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 and not alm)
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,
autolm,
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/gutenberg_27045.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()
|