Commit
·
74edfc7
1
Parent(s):
d30820d
Update README.md
Browse files
README.md
CHANGED
|
@@ -18,7 +18,7 @@ metrics:
|
|
| 18 |
|
| 19 |
This repository provides all the necessary tools to perform automatic speech
|
| 20 |
recognition from an end-to-end system pretrained on CommonVoice (FR) within
|
| 21 |
-
SpeechBrain. For a better experience we encourage you to learn more about
|
| 22 |
[SpeechBrain](https://speechbrain.github.io). The given ASR model performance are:
|
| 23 |
|
| 24 |
| Release | Test CER | Test WER | GPUs |
|
|
@@ -27,19 +27,19 @@ SpeechBrain. For a better experience we encourage you to learn more about
|
|
| 27 |
|
| 28 |
## Pipeline description
|
| 29 |
|
| 30 |
-
This ASR system is composed
|
| 31 |
1. Tokenizer (unigram) that transforms words into subword units and trained with
|
| 32 |
the train transcriptions (train.tsv) of CommonVoice (FR).
|
| 33 |
3. Acoustic model (CRDNN + CTC/Attention). The CRDNN architecture is made of
|
| 34 |
-
N blocks of convolutional neural networks with
|
| 35 |
frequency domain. Then, a bidirectional LSTM is connected to a final DNN to obtain
|
| 36 |
the final acoustic representation that is given to the CTC and attention decoders.
|
| 37 |
|
| 38 |
## Intended uses & limitations
|
| 39 |
|
| 40 |
-
This model has been
|
| 41 |
for the French language. Thanks to the flexibility of SpeechBrain, any of the 2 blocks
|
| 42 |
-
detailed above can be extracted and connected to
|
| 43 |
installed.
|
| 44 |
|
| 45 |
## Install SpeechBrain
|
|
|
|
| 18 |
|
| 19 |
This repository provides all the necessary tools to perform automatic speech
|
| 20 |
recognition from an end-to-end system pretrained on CommonVoice (FR) within
|
| 21 |
+
SpeechBrain. For a better experience, we encourage you to learn more about
|
| 22 |
[SpeechBrain](https://speechbrain.github.io). The given ASR model performance are:
|
| 23 |
|
| 24 |
| Release | Test CER | Test WER | GPUs |
|
|
|
|
| 27 |
|
| 28 |
## Pipeline description
|
| 29 |
|
| 30 |
+
This ASR system is composed of 2 different but linked blocks:
|
| 31 |
1. Tokenizer (unigram) that transforms words into subword units and trained with
|
| 32 |
the train transcriptions (train.tsv) of CommonVoice (FR).
|
| 33 |
3. Acoustic model (CRDNN + CTC/Attention). The CRDNN architecture is made of
|
| 34 |
+
N blocks of convolutional neural networks with normalization and pooling on the
|
| 35 |
frequency domain. Then, a bidirectional LSTM is connected to a final DNN to obtain
|
| 36 |
the final acoustic representation that is given to the CTC and attention decoders.
|
| 37 |
|
| 38 |
## Intended uses & limitations
|
| 39 |
|
| 40 |
+
This model has been primarily developed to be run within SpeechBrain as a pretrained ASR model
|
| 41 |
for the French language. Thanks to the flexibility of SpeechBrain, any of the 2 blocks
|
| 42 |
+
detailed above can be extracted and connected to your custom pipeline as long as SpeechBrain is
|
| 43 |
installed.
|
| 44 |
|
| 45 |
## Install SpeechBrain
|