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DeepSpeech
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f2929415
编写于
10月 13, 2022
作者:
T
tianhao zhang
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update reference.md and released_model.md
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docs/source/reference.md
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f2929415
...
...
@@ -28,6 +28,8 @@ We borrowed a lot of code from these repos to build `model` and `engine`, thanks
*
[
speechbrain
](
https://github.com/speechbrain/speechbrain/blob/develop/LICENSE
)
-
Apache-2.0 License
-
ECAPA-TDNN SV model
-
ASR with CTC and pre-trained wav2vec2 models.
*
[
chainer
](
https://github.com/chainer/chainer/blob/master/LICENSE
)
-
MIT License
...
...
@@ -43,3 +45,7 @@ We borrowed a lot of code from these repos to build `model` and `engine`, thanks
*
[
g2pW
](
https://github.com/GitYCC/g2pW/blob/master/LICENCE
)
-
Apache-2.0 license
*
[
transformers
](
https://github.com/huggingface/transformers
)
-
Apache-2.0 License
-
Wav2vec2.0
\ No newline at end of file
docs/source/released_model.md
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f2929415
...
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@@ -17,8 +17,12 @@ Acoustic Model | Training Data | Token-based | Size | Descriptions | CER | WER |
[
Conformer Librispeech ASR1 Model
](
https://paddlespeech.bj.bcebos.com/s2t/librispeech/asr1/asr1_conformer_librispeech_ckpt_0.1.1.model.tar.gz
)
| Librispeech Dataset | subword-based | 191 MB | Encoder:Conformer, Decoder:Transformer, Decoding method: Attention rescoring |-| 0.0338 | 960 h |
[
Conformer Librispeech ASR1
](
../../examples/librispeech/asr1
)
| python |
[
Transformer Librispeech ASR1 Model
](
https://paddlespeech.bj.bcebos.com/s2t/librispeech/asr1/asr1_transformer_librispeech_ckpt_0.1.1.model.tar.gz
)
| Librispeech Dataset | subword-based | 131 MB | Encoder:Transformer, Decoder:Transformer, Decoding method: Attention rescoring |-| 0.0381 | 960 h |
[
Transformer Librispeech ASR1
](
../../examples/librispeech/asr1
)
| python |
[
Transformer Librispeech ASR2 Model
](
https://paddlespeech.bj.bcebos.com/s2t/librispeech/asr2/asr2_transformer_librispeech_ckpt_0.1.1.model.tar.gz
)
| Librispeech Dataset | subword-based | 131 MB | Encoder:Transformer, Decoder:Transformer, Decoding method: JoinCTC w/ LM |-| 0.0240 | 960 h |
[
Transformer Librispeech ASR2
](
../../examples/librispeech/asr2
)
| python |
[
Wav2vec2-large-960h-lv60-self Model
](
https://paddlespeech.bj.bcebos.com/wav2vec/wav2vec2-large-960h-lv60-self.pdparams
)
| Librispeech and LV-60k Dataset | - | 1.18 GB | Pre-trained Wav2vec2.0 Model |-| - | 5.3w h |
[
Wav2vecASR Librispeech ASR3
](
../../examples/librispeech/asr3
)
| python |
[
Wav2vec2ASR-large-960h-librispeech Model
](
https://paddlespeech.bj.bcebos.com/s2t/librispeech/asr3/wav2vec2ASR-large-960h-librispeech_ckpt_1.3.0.model.tar.gz
)
| Librispeech | - | 1.18 GB | Encoder:Wav2vec2.0, Decoder:CTC, Decoding method: Greedy search |-| 0.0189 | 960 h |
[
Wav2vecASR Librispeech ASR3
](
../../examples/librispeech/asr3
)
| python |
### Self-Supervised Pre-trained Model
Model | Pre-Train Method | Pre-Train Data | Finetune Data | Size | Descriptions | CER | WER | Example Link |
:-------------:| :------------:| :-----: | -----: | :-----: |:-----:| :-----: | :-----: | :-----: |
[
Wav2vec2-large-960h-lv60-self Model
](
https://paddlespeech.bj.bcebos.com/wav2vec/wav2vec2-large-960h-lv60-self.pdparams
)
| wav2vec2 | Librispeech and LV-60k Dataset (5.3w h) | - | 1.18 GB |Pre-trained Wav2vec2.0 Model | - | - | - |
[
Wav2vec2ASR-large-960h-librispeech Model
](
https://paddlespeech.bj.bcebos.com/s2t/librispeech/asr3/wav2vec2ASR-large-960h-librispeech_ckpt_1.3.0.model.tar.gz
)
| wav2vec2 | Librispeech and LV-60k Dataset (5.3w h) | Librispeech (960 h) | 1.18 GB |Encoder: Wav2vec2.0, Decoder: CTC, Decoding method: Greedy search | - | 0.0189 |
[
Wav2vecASR Librispeech ASR3
](
../../examples/librispeech/asr3
)
|
### Language Model based on NGram
Language Model | Training Data | Token-based | Size | Descriptions
...
...
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