speechbrainteam commited on
Commit
3604471
1 Parent(s): fecb430

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +16 -28
README.md CHANGED
@@ -4,13 +4,12 @@ thumbnail:
4
  tags:
5
  - speechbrain
6
  - embeddings
7
- - Sound
8
- - Keywords
9
- - Keyword Spotting
10
  - pytorch
11
  - ECAPA-TDNN
12
  - TDNN
13
- - Command Recognition
14
  license: "apache-2.0"
15
  datasets:
16
  - Urbansound8k
@@ -19,27 +18,27 @@ metrics:
19
 
20
  ---
21
 
22
- # WORK IN PROGRESS
23
 
24
  <iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe>
25
  <br/><br/>
26
 
27
- # Command Recognition with ECAPA embeddings on UrbanSoudnd8k
28
 
29
- This repository provides all the necessary tools to perform sound recognition with SpeechBrain using a model pretrained on UrbanSound8k.
30
- You can download the dataset [here](https://urbansounddataset.weebly.com/urbansound8k.html)
31
- The provided system can recognize the following 10 keywords:
32
- ```
33
 
34
- dog_bark, children_playing, air_conditioner, street_music, gun_shot, siren, engine_idling, jackhammer, drilling, car_horn
 
35
  ```
36
 
37
  For a better experience, we encourage you to learn more about
38
  [SpeechBrain](https://speechbrain.github.io). The given model performance on the test set is:
39
 
40
- | Release | Accuracy 1-fold (%)
41
  |:-------------:|:--------------:|
42
- | 04-06-21 | 75.5 |
43
 
44
 
45
  ## Pipeline description
@@ -56,7 +55,7 @@ pip install speechbrain
56
  Please notice that we encourage you to read our tutorials and learn more about
57
  [SpeechBrain](https://speechbrain.github.io).
58
 
59
- ### Perform Sound Recognition
60
 
61
  ```python
62
  import torchaudio
@@ -75,7 +74,7 @@ print(text_lab)
75
  To perform inference on the GPU, add `run_opts={"device":"cuda"}` when calling the `from_hparams` method.
76
 
77
  ### Training
78
- The model was trained with SpeechBrain (8cab8b0c).
79
  To train it from scratch follows these steps:
80
  1. Clone SpeechBrain:
81
  ```bash
@@ -90,11 +89,11 @@ pip install -e .
90
 
91
  3. Run Training:
92
  ```
93
- cd recipes/UrbanSound8k/SoundClassification
94
  python train.py hparams/train_ecapa_tdnn.yaml --data_folder=your_data_folder
95
  ```
96
 
97
- You can find our training results (models, logs, etc) [here](https://drive.google.com/drive/folders/1sItfg_WNuGX6h2dCs8JTGq2v2QoNTaUg?usp=sharing).
98
 
99
  ### Limitations
100
  The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.
@@ -116,17 +115,6 @@ The SpeechBrain team does not provide any warranty on the performance achieved b
116
  }
117
  ```
118
 
119
- #### Referencing UrbanSound
120
- ```@inproceedings{Salamon:UrbanSound:ACMMM:14,
121
- Author = {Salamon, J. and Jacoby, C. and Bello, J. P.},
122
- Booktitle = {22nd {ACM} International Conference on Multimedia (ACM-MM'14)},
123
- Month = {Nov.},
124
- Pages = {1041--1044},
125
- Title = {A Dataset and Taxonomy for Urban Sound Research},
126
- Year = {2014}}
127
- ```
128
-
129
-
130
 
131
  # **Citing SpeechBrain**
132
  Please, cite SpeechBrain if you use it for your research or business.
 
4
  tags:
5
  - speechbrain
6
  - embeddings
7
+ - Language
8
+ - Identification
 
9
  - pytorch
10
  - ECAPA-TDNN
11
  - TDNN
12
+ - CommonLanguage
13
  license: "apache-2.0"
14
  datasets:
15
  - Urbansound8k
 
18
 
19
  ---
20
 
 
21
 
22
  <iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe>
23
  <br/><br/>
24
 
25
+ # Language Identification from Speech Recordings with ECAPA embeddings on CommonLanguage
26
 
27
+ This repository provides all the necessary tools to perform language identification from speeech recordinfs with SpeechBrain.
28
+ The system uses a model pretrained on the CommonLanguage dataset (45 languages).
29
+ You can download the dataset [here](https://zenodo.org/record/5036977#.YNzDbXVKg5k)
30
+ The provided system can recognize the following 45 languages from short speech recordings:
31
 
32
+ ```
33
+ Arabic, Basque, Breton, Catalan, Chinese_China, Chinese_Hongkong, Chinese_Taiwan, Chuvash, Czech, Dhivehi, Dutch, English, Esperanto, Estonian, French, Frisian, Georgian, German, Greek, Hakha_Chin, Indonesian, Interlingua, Italian, Japanese, Kabyle, Kinyarwanda, Kyrgyz, Latvian, Maltese, Mangolian, Persian, Polish, Portuguese, Romanian, Romansh_Sursilvan, Russian, Sakha, Slovenian, Spanish, Swedish, Tamil, Tatar, Turkish, Ukranian, Welsh
34
  ```
35
 
36
  For a better experience, we encourage you to learn more about
37
  [SpeechBrain](https://speechbrain.github.io). The given model performance on the test set is:
38
 
39
+ | Release | Accuracy (%)
40
  |:-------------:|:--------------:|
41
+ | 30-06-21 | 15.1 |
42
 
43
 
44
  ## Pipeline description
 
55
  Please notice that we encourage you to read our tutorials and learn more about
56
  [SpeechBrain](https://speechbrain.github.io).
57
 
58
+ ### Perform Language Identification from Speech Recordings
59
 
60
  ```python
61
  import torchaudio
 
74
  To perform inference on the GPU, add `run_opts={"device":"cuda"}` when calling the `from_hparams` method.
75
 
76
  ### Training
77
+ The model was trained with SpeechBrain (a02f860e).
78
  To train it from scratch follows these steps:
79
  1. Clone SpeechBrain:
80
  ```bash
 
89
 
90
  3. Run Training:
91
  ```
92
+ cd recipes/CommonLanguage/lang_id
93
  python train.py hparams/train_ecapa_tdnn.yaml --data_folder=your_data_folder
94
  ```
95
 
96
+ You can find our training results (models, logs, etc) [here](https://drive.google.com/drive/folders/1sD2u0MhSmJlx_3RRgwsYzevX81RM8-WE?usp=sharing).
97
 
98
  ### Limitations
99
  The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.
 
115
  }
116
  ```
117
 
 
 
 
 
 
 
 
 
 
 
 
118
 
119
  # **Citing SpeechBrain**
120
  Please, cite SpeechBrain if you use it for your research or business.