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void-emb-demo
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add app.py

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  1. app.py +83 -0
  2. requirements.txt +334 -0
app.py ADDED
@@ -0,0 +1,83 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ """
2
+ This code is for testing and demonstration.
3
+ Source code for credit: https://huggingface.co/spaces/nithinraok/titanet-speaker-verification/blob/main/app.py
4
+ """
5
+
6
+ import gradio as gr
7
+ import torch
8
+ from nemo.collections.asr.models import EncDecSpeakerLabelModel
9
+
10
+ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
11
+ model_name = "nvidia/speakerverification_en_titanet_large"
12
+ model = EncDecSpeakerLabelModel.from_pretrained(model_name).to(device)
13
+
14
+ def compare(path1, path2):
15
+ if not (path1 and path2):
16
+ raise gr.Error("Need recordings from both speakers!")
17
+
18
+ embs1 = model.get_embedding(path1).squeeze()
19
+ embs2 = model.get_embedding(path2).squeeze()
20
+
21
+ #Length Normalize
22
+ X = embs1 / torch.linalg.norm(embs1)
23
+ Y = embs2 / torch.linalg.norm(embs2)
24
+
25
+ # Score
26
+ similarity_score = torch.dot(X, Y) / ((torch.dot(X, X) * torch.dot(Y, Y)) ** 0.5)
27
+ similarity_score = (similarity_score + 1) / 2
28
+
29
+ # # Decision
30
+ # if similarity_score >= THRESHOLD:
31
+ # return OUTPUT_OK.format(similarity_score * 100)
32
+ # else:
33
+ # return OUTPUT_FAIL.format(similarity_score * 100)
34
+ return "{:.4f}".format(similarity_score.item())
35
+
36
+
37
+ inputs = [
38
+ gr.inputs.Audio(source="microphone", type="filepath", optional=True, label="Speaker #1"),
39
+ gr.inputs.Audio(source="microphone", type="filepath", optional=True, label="Speaker #2"),
40
+ ]
41
+
42
+ upload_inputs = [
43
+ gr.inputs.Audio(source="upload", type="filepath", optional=True, label="Speaker #1"),
44
+ gr.inputs.Audio(source="upload", type="filepath", optional=True, label="Speaker #2"),
45
+ ]
46
+
47
+ description = (
48
+ "The purpose of this demo is to show how VoID could work with speech embeddings rather than mel spectograms.\n"
49
+ "This demonstration will analyze two recordings of speech and ascertain whether they have been spoken by the same individual.\n"
50
+ "You can attempt this exercise using your own voice."
51
+ )
52
+
53
+ title="VoID with TitaNet Embeddings"
54
+
55
+ microphone_interface = gr.Interface(
56
+ fn=compare,
57
+ inputs=inputs,
58
+ outputs="text",
59
+ title=title,
60
+ description=description,
61
+ layout="horizontal",
62
+ theme="huggingface",
63
+ allow_flagging=False,
64
+ live=False,
65
+ # examples=examples,
66
+ )
67
+
68
+ upload_interface = gr.Interface(
69
+ fn=compare,
70
+ inputs=upload_inputs,
71
+ outputs="text",
72
+ title=title,
73
+ description=description,
74
+ layout="horizontal",
75
+ theme="huggingface",
76
+ allow_flagging=False,
77
+ live=False,
78
+ # examples=examples,
79
+ )
80
+
81
+ demo = gr.TabbedInterface([microphone_interface, upload_interface], ["Microphone", "Upload File"])
82
+
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+ demo.launch()
requirements.txt ADDED
@@ -0,0 +1,334 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ nbconvert @ file:///private/var/folders/nz/j6p8yfhx1mv_0grj5xl4650h0000gp/T/abs_36au3u9s44/croot/nbconvert_1668450648628/work
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+ nbformat @ file:///private/var/folders/nz/j6p8yfhx1mv_0grj5xl4650h0000gp/T/abs_94781rq_cg/croot/nbformat_1670352348390/work
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+ notebook_shim @ file:///private/var/folders/nz/j6p8yfhx1mv_0grj5xl4650h0000gp/T/abs_f8mr1gjfb7/croot/notebook-shim_1668160580414/work
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184
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+ ply==3.11
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+ progress==1.6
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+ prompt-toolkit @ file:///private/var/folders/nz/j6p8yfhx1mv_0grj5xl4650h0000gp/T/abs_0blbsngvis/croot/prompt-toolkit_1672387317724/work
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+ pydub==0.25.1
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+ pynini @ file:///Users/runner/miniforge3/conda-bld/pynini_1667113552673/work
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+ pyOpenSSL @ file:///private/var/folders/nz/j6p8yfhx1mv_0grj5xl4650h0000gp/T/abs_38h4axtq38/croot/pyopenssl_1677607699670/work
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+ pyparsing @ file:///private/var/folders/nz/j6p8yfhx1mv_0grj5xl4650h0000gp/T/abs_3b_3vxnd07/croots/recipe/pyparsing_1661452540919/work
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+ pypinyin-dict==0.6.0
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+ PySocks @ file:///Users/ktietz/Code/oss/ci_pkgs/pysocks_1626781349491/work
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+ QtPy @ file:///private/var/folders/nz/j6p8yfhx1mv_0grj5xl4650h0000gp/T/abs_90hl8ymlpx/croots/recipe/qtpy_1662014534092/work
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+ rapidfuzz @ file:///private/var/folders/nz/j6p8yfhx1mv_0grj5xl4650h0000gp/T/abs_24x93akdfk/croot/rapidfuzz_1679593472383/work
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+ readchar @ file:///home/conda/feedstock_root/build_artifacts/readchar_1679045163536/work
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+ regex @ file:///private/var/folders/nz/j6p8yfhx1mv_0grj5xl4650h0000gp/T/abs_c16d2a8a-126e-4d7e-8084-357d1f1d1103zj2vwnhn/croots/recipe/regex_1658257182710/work
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+ rich @ file:///private/var/folders/nz/j6p8yfhx1mv_0grj5xl4650h0000gp/T/abs_f2payco56o/croot/rich_1684282180753/work
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+ rsa==4.9
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+ sip @ file:///private/var/folders/nz/j6p8yfhx1mv_0grj5xl4650h0000gp/T/abs_fbqiv4bzwo/croots/recipe/sip_1659012372184/work
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+ sortedcontainers==2.4.0
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280
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286
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318
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+ webdataset==0.1.62
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325
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