add AIBOM
#30
by
sabato-nocera
- opened
- nvidia_canary-1b.json +649 -0
nvidia_canary-1b.json
ADDED
@@ -0,0 +1,649 @@
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1 |
+
{
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2 |
+
"bomFormat": "CycloneDX",
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3 |
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"specVersion": "1.6",
|
4 |
+
"serialNumber": "urn:uuid:dd499724-872b-4392-817f-8511a1cd9113",
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5 |
+
"version": 1,
|
6 |
+
"metadata": {
|
7 |
+
"timestamp": "2025-06-05T09:37:28.708234+00:00",
|
8 |
+
"component": {
|
9 |
+
"type": "machine-learning-model",
|
10 |
+
"bom-ref": "nvidia/canary-1b-58688bd0-57c9-5752-b615-3abc9265c7a1",
|
11 |
+
"name": "nvidia/canary-1b",
|
12 |
+
"externalReferences": [
|
13 |
+
{
|
14 |
+
"url": "https://huggingface.co/nvidia/canary-1b",
|
15 |
+
"type": "documentation"
|
16 |
+
}
|
17 |
+
],
|
18 |
+
"modelCard": {
|
19 |
+
"modelParameters": {
|
20 |
+
"task": "automatic-speech-recognition",
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21 |
+
"datasets": [
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22 |
+
{
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23 |
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"ref": "librispeech_asr-7baf0ed9-b50c-5f93-8c23-49a2b8749c19"
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24 |
+
},
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25 |
+
{
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26 |
+
"ref": "fisher_corpus-a0c6e2c1-e876-5c66-89b2-cb93697b2a1c"
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27 |
+
},
|
28 |
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{
|
29 |
+
"ref": "Switchboard-1-b54b0d1d-3005-514e-9668-98d3c19f793f"
|
30 |
+
},
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31 |
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{
|
32 |
+
"ref": "WSJ-0-095442e6-ea65-5f6d-b360-432c7a2f501d"
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33 |
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},
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34 |
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{
|
35 |
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"ref": "WSJ-1-0ef003e6-350d-50bb-9df7-9491b0c9b0b3"
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36 |
+
},
|
37 |
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{
|
38 |
+
"ref": "National-Singapore-Corpus-Part-1-1fbb2914-35aa-5126-9a84-a8b77169254c"
|
39 |
+
},
|
40 |
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{
|
41 |
+
"ref": "National-Singapore-Corpus-Part-6-4f83cf7f-3026-5a77-ae37-28a73d4abc24"
|
42 |
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},
|
43 |
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{
|
44 |
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"ref": "vctk-d80444bd-bcc6-5c25-8570-061bb96dae38"
|
45 |
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},
|
46 |
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{
|
47 |
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"ref": "voxpopuli-15fb6343-a710-54f9-842b-3a1b43d6a630"
|
48 |
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},
|
49 |
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{
|
50 |
+
"ref": "europarl-7e07ffed-425e-5e05-8847-08a1899f0ac1"
|
51 |
+
},
|
52 |
+
{
|
53 |
+
"ref": "multilingual_librispeech-f260ef31-1d5d-54fe-8e61-88c397c0b7ce"
|
54 |
+
},
|
55 |
+
{
|
56 |
+
"ref": "mozilla-foundation/common_voice_8_0-a994a71f-f9f5-5f65-a3fa-51a56293cd8e"
|
57 |
+
},
|
58 |
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{
|
59 |
+
"ref": "MLCommons/peoples_speech-f88dc766-1de0-51c6-865d-16930ec19be6"
|
60 |
+
}
|
61 |
+
]
|
62 |
+
},
|
63 |
+
"properties": [
|
64 |
+
{
|
65 |
+
"name": "library_name",
|
66 |
+
"value": "nemo"
|
67 |
+
}
|
68 |
+
],
|
69 |
+
"quantitativeAnalysis": {
|
70 |
+
"performanceMetrics": [
|
71 |
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{
|
72 |
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"slice": "dataset: librispeech_asr, split: test, config: other",
|
73 |
+
"type": "wer",
|
74 |
+
"value": 2.89
|
75 |
+
},
|
76 |
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{
|
77 |
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"slice": "dataset: kensho/spgispeech, split: test, config: test",
|
78 |
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"type": "wer",
|
79 |
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"value": 4.79
|
80 |
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},
|
81 |
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{
|
82 |
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"slice": "dataset: mozilla-foundation/common_voice_16_1, split: test, config: en",
|
83 |
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"type": "wer",
|
84 |
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"value": 7.97
|
85 |
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},
|
86 |
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{
|
87 |
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"slice": "dataset: mozilla-foundation/common_voice_16_1, split: test, config: de",
|
88 |
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"type": "wer",
|
89 |
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"value": 4.61
|
90 |
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},
|
91 |
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{
|
92 |
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"slice": "dataset: mozilla-foundation/common_voice_16_1, split: test, config: es",
|
93 |
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"type": "wer",
|
94 |
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"value": 3.99
|
95 |
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},
|
96 |
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{
|
97 |
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"slice": "dataset: mozilla-foundation/common_voice_16_1, split: test, config: fr",
|
98 |
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"type": "wer",
|
99 |
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"value": 6.53
|
100 |
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},
|
101 |
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{
|
102 |
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"slice": "dataset: google/fleurs, split: test, config: en_us",
|
103 |
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"type": "bleu",
|
104 |
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"value": 32.15
|
105 |
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},
|
106 |
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{
|
107 |
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"slice": "dataset: google/fleurs, split: test, config: en_us",
|
108 |
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"type": "bleu",
|
109 |
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"value": 22.66
|
110 |
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},
|
111 |
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{
|
112 |
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"slice": "dataset: google/fleurs, split: test, config: en_us",
|
113 |
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"type": "bleu",
|
114 |
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"value": 40.76
|
115 |
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},
|
116 |
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{
|
117 |
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"slice": "dataset: google/fleurs, split: test, config: de_de",
|
118 |
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"type": "bleu",
|
119 |
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"value": 33.98
|
120 |
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},
|
121 |
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{
|
122 |
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"slice": "dataset: google/fleurs, split: test, config: es_419",
|
123 |
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"type": "bleu",
|
124 |
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"value": 21.8
|
125 |
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},
|
126 |
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{
|
127 |
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"slice": "dataset: google/fleurs, split: test, config: fr_fr",
|
128 |
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"type": "bleu",
|
129 |
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"value": 30.95
|
130 |
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},
|
131 |
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{
|
132 |
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"slice": "dataset: covost2, split: test, config: de_de",
|
133 |
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"type": "bleu",
|
134 |
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"value": 37.67
|
135 |
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},
|
136 |
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{
|
137 |
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"slice": "dataset: covost2, split: test, config: es_419",
|
138 |
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"type": "bleu",
|
139 |
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"value": 40.7
|
140 |
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},
|
141 |
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{
|
142 |
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"slice": "dataset: covost2, split: test, config: fr_fr",
|
143 |
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"type": "bleu",
|
144 |
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"value": 40.42
|
145 |
+
}
|
146 |
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]
|
147 |
+
}
|
148 |
+
},
|
149 |
+
"authors": [
|
150 |
+
{
|
151 |
+
"name": "nvidia"
|
152 |
+
}
|
153 |
+
],
|
154 |
+
"licenses": [
|
155 |
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{
|
156 |
+
"license": {
|
157 |
+
"id": "CC-BY-NC-4.0",
|
158 |
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"url": "https://spdx.org/licenses/CC-BY-NC-4.0.html"
|
159 |
+
}
|
160 |
+
}
|
161 |
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],
|
162 |
+
"tags": [
|
163 |
+
"nemo",
|
164 |
+
"automatic-speech-recognition",
|
165 |
+
"automatic-speech-translation",
|
166 |
+
"speech",
|
167 |
+
"audio",
|
168 |
+
"Transformer",
|
169 |
+
"FastConformer",
|
170 |
+
"Conformer",
|
171 |
+
"pytorch",
|
172 |
+
"NeMo",
|
173 |
+
"hf-asr-leaderboard",
|
174 |
+
"en",
|
175 |
+
"de",
|
176 |
+
"es",
|
177 |
+
"fr",
|
178 |
+
"dataset:librispeech_asr",
|
179 |
+
"dataset:fisher_corpus",
|
180 |
+
"dataset:Switchboard-1",
|
181 |
+
"dataset:WSJ-0",
|
182 |
+
"dataset:WSJ-1",
|
183 |
+
"dataset:National-Singapore-Corpus-Part-1",
|
184 |
+
"dataset:National-Singapore-Corpus-Part-6",
|
185 |
+
"dataset:vctk",
|
186 |
+
"dataset:voxpopuli",
|
187 |
+
"dataset:europarl",
|
188 |
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"dataset:multilingual_librispeech",
|
189 |
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"dataset:mozilla-foundation/common_voice_8_0",
|
190 |
+
"dataset:MLCommons/peoples_speech",
|
191 |
+
"arxiv:2305.05084",
|
192 |
+
"arxiv:1706.03762",
|
193 |
+
"license:cc-by-nc-4.0",
|
194 |
+
"model-index",
|
195 |
+
"region:us"
|
196 |
+
]
|
197 |
+
}
|
198 |
+
},
|
199 |
+
"components": [
|
200 |
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{
|
201 |
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"type": "data",
|
202 |
+
"bom-ref": "librispeech_asr-7baf0ed9-b50c-5f93-8c23-49a2b8749c19",
|
203 |
+
"name": "librispeech_asr",
|
204 |
+
"data": [
|
205 |
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{
|
206 |
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"type": "dataset",
|
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"value": "Name of the dataset subset: dirty {\"split\": \"train\", \"path\": \"dirty/train-*\"}, {\"split\": \"validation\", \"path\": \"dirty/validation-*\"}, {\"split\": \"test\", \"path\": \"dirty/test-*\"}"
|
611 |
+
},
|
612 |
+
{
|
613 |
+
"name": "configs",
|
614 |
+
"value": "Name of the dataset subset: dirty_sa {\"split\": \"train\", \"path\": \"dirty_sa/train-*\"}, {\"split\": \"validation\", \"path\": \"dirty_sa/validation-*\"}, {\"split\": \"test\", \"path\": \"dirty_sa/test-*\"}"
|
615 |
+
},
|
616 |
+
{
|
617 |
+
"name": "configs",
|
618 |
+
"value": "Name of the dataset subset: microset {\"split\": \"train\", \"path\": \"microset/train-*\"}"
|
619 |
+
},
|
620 |
+
{
|
621 |
+
"name": "configs",
|
622 |
+
"value": "Name of the dataset subset: test {\"split\": \"test\", \"path\": \"test/test-*\"}"
|
623 |
+
},
|
624 |
+
{
|
625 |
+
"name": "configs",
|
626 |
+
"value": "Name of the dataset subset: validation {\"split\": \"validation\", \"path\": \"validation/validation-*\"}"
|
627 |
+
},
|
628 |
+
{
|
629 |
+
"name": "license",
|
630 |
+
"value": "cc-by-2.0, cc-by-2.5, cc-by-3.0, cc-by-4.0, cc-by-sa-3.0, cc-by-sa-4.0"
|
631 |
+
}
|
632 |
+
]
|
633 |
+
},
|
634 |
+
"governance": {
|
635 |
+
"owners": [
|
636 |
+
{
|
637 |
+
"organization": {
|
638 |
+
"name": "MLCommons",
|
639 |
+
"url": "https://huggingface.co/MLCommons"
|
640 |
+
}
|
641 |
+
}
|
642 |
+
]
|
643 |
+
},
|
644 |
+
"description": "\n\t\n\t\t\n\t\tDataset Card for People's Speech\n\t\n\n\n\t\n\t\t\n\t\tDataset Summary\n\t\n\nThe People's Speech Dataset is among the world's largest English speech recognition corpus today that is licensed for academic and commercial usage under CC-BY-SA and CC-BY 4.0. It includes 30,000+ hours of transcribed speech in English languages with a diverse set of speakers. This open dataset is large enough to train speech-to-text systems and crucially is available with a permissive license.\n\n\t\n\t\t\n\t\n\t\n\t\tSupported Tasks\u2026 See the full description on the dataset page: https://huggingface.co/datasets/MLCommons/peoples_speech."
|
645 |
+
}
|
646 |
+
]
|
647 |
+
}
|
648 |
+
]
|
649 |
+
}
|