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d31dbabb
编写于
1月 12, 2022
作者:
J
Jackwaterveg
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GitHub
1月 12, 2022
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[Doc] Update released model for r0.1.1 (#1316)
* updated ASR released model * update the doc, test=doc_fix
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@@ -5,14 +5,13 @@
### Speech Recognition Model
Acoustic Model | Training Data | Token-based | Size | Descriptions | CER | WER | Hours of speech | Example Link
:-------------:| :------------:| :-----: | -----: | :-----: |:-----:| :-----: | :-----: | :-----:
[
Ds2 Online Aishell ASR0 Model
](
https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/aishell_ds2_online_cer8.00_release.tar.gz
)
| Aishell Dataset | Char-based | 345 MB | 2 Conv + 5 LSTM layers with only forward direction | 0.080 |-| 151 h |
[
D2 Online Aishell ASR0
](
../../examples/aishell/asr0
)
[
Ds2 Offline Aishell ASR0 Model
](
https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/ds2.model.tar.gz
)
| Aishell Dataset | Char-based | 306 MB | 2 Conv + 3 bidirectional GRU layers| 0.064 |-| 151 h |
[
Ds2 Offline Aishell ASR0
](
../../examples/aishell/asr0
)
[
Conformer Online Aishell ASR1 Model
](
https://deepspeech.bj.bcebos.com/release2.1/aishell/s1/aishell.chunk.release.tar.gz
)
| Aishell Dataset | Char-based | 283 MB | Encoder:Conformer, Decoder:Transformer, Decoding method: Attention rescoring | 0.0594 |-| 151 h |
[
Conformer Online Aishell ASR1
](
../../examples/aishell/asr1
)
[
Conformer Offline Aishell ASR1 Model
](
https://deepspeech.bj.bcebos.com/release2.1/aishell/s1/aishell.release.tar.gz
)
| Aishell Dataset | Char-based | 284 MB | Encoder:Conformer, Decoder:Transformer, Decoding method: Attention rescoring | 0.0547 |-| 151 h |
[
Conformer Offline Aishell ASR1
](
../../examples/aishell/asr1
)
[
Transformer Aishell ASR1 Model
](
https://paddlespeech.bj.bcebos.com/s2t/aishell/asr1/transformer.model.tar.gz
)
| Aishell Dataset | Char-based | 128 MB | Encoder:Transformer, Decoder:Transformer, Decoding method: Attention rescoring | 0.0523 || 151 h |
[
Transformer Aishell ASR1
](
../../examples/aishell/asr1
)
[
Conformer Librispeech ASR1 Model
](
https://paddlespeech.bj.bcebos.com/s2t/librispeech/asr1/conformer.model.tar.gz
)
| Librispeech Dataset | subword-based | 191 MB | Encoder:Conformer, Decoder:Transformer, Decoding method: Attention rescoring |-| 0.0337 | 960 h |
[
Conformer Librispeech ASR1
](
../../example/librispeech/asr1
)
[
Transformer Librispeech ASR1 Model
](
https://paddlespeech.bj.bcebos.com/s2t/librispeech/asr1/transformer.model.tar.gz
)
| Librispeech Dataset | subword-based | 131 MB | Encoder:Transformer, Decoder:Transformer, Decoding method: Attention rescoring |-| 0.0381 | 960 h |
[
Transformer Librispeech ASR1
](
../../example/librispeech/asr1
)
[
Transformer Librispeech ASR2 Model
](
https://paddlespeech.bj.bcebos.com/s2t/librispeech/asr2/transformer.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
](
../../example/librispeech/asr2
)
[
Ds2 Online Aishell ASR0 Model
](
https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/asr0_deepspeech2_online_aishell_ckpt_0.1.1.model.tar.gz
)
| Aishell Dataset | Char-based | 345 MB | 2 Conv + 5 LSTM layers with only forward direction | 0.080 |-| 151 h |
[
D2 Online Aishell ASR0
](
../../examples/aishell/asr0
)
[
Ds2 Offline Aishell ASR0 Model
](
https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/asr0_deepspeech2_aishell_ckpt_0.1.1.model.tar.gz
)
| Aishell Dataset | Char-based | 306 MB | 2 Conv + 3 bidirectional GRU layers| 0.064 |-| 151 h |
[
Ds2 Offline Aishell ASR0
](
../../examples/aishell/asr0
)
[
Conformer Offline Aishell ASR1 Model
](
https://paddlespeech.bj.bcebos.com/s2t/aishell/asr1/asr1_conformer_aishell_ckpt_0.1.1.model.tar.gz
)
| Aishell Dataset | Char-based | 284 MB | Encoder:Conformer, Decoder:Transformer, Decoding method: Attention rescoring | 0.056 |-| 151 h |
[
Conformer Offline Aishell ASR1
](
../../examples/aishell/asr1
)
[
Transformer Aishell ASR1 Model
](
https://paddlespeech.bj.bcebos.com/s2t/aishell/asr1/asr1_transformer_aishell_ckpt_0.1.1.model.tar.gz
)
| Aishell Dataset | Char-based | 128 MB | Encoder:Transformer, Decoder:Transformer, Decoding method: Attention rescoring | 0.0523 || 151 h |
[
Transformer Aishell ASR1
](
../../examples/aishell/asr1
)
[
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 |-| 0.0337 | 960 h |
[
Conformer Librispeech ASR1
](
../../example/librispeech/asr1
)
[
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
](
../../example/librispeech/asr1
)
[
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
](
../../example/librispeech/asr2
)
### Language Model based on NGram
Language Model | Training Data | Token-based | Size | Descriptions
...
...
@@ -25,7 +24,7 @@ Language Model | Training Data | Token-based | Size | Descriptions
| Model | Training Data | Token-based | Size | Descriptions | BLEU | Example Link |
| :-----: | :-----: | :-----: | :-----: | :-----: | :-----: | :-----: |
|
[
Transformer FAT-ST MTL En-Zh
](
https://paddlespeech.bj.bcebos.com/s2t/ted_en_zh/st1/
fat_st_ted-en-zh
.tar.gz
)
| Ted-En-Zh| Spm| | Encoder:Transformer, Decoder:Transformer,
<br
/>
Decoding method: Attention | 20.80 |
[
Transformer Ted-En-Zh ST1
](
https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/examples/ted_en_zh/st1
)
|
|
[
Transformer FAT-ST MTL En-Zh
](
https://paddlespeech.bj.bcebos.com/s2t/ted_en_zh/st1/
st1_transformer_mtl_noam_ted-en-zh_ckpt_0.1.1.model
.tar.gz
)
| Ted-En-Zh| Spm| | Encoder:Transformer, Decoder:Transformer,
<br
/>
Decoding method: Attention | 20.80 |
[
Transformer Ted-En-Zh ST1
](
https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/examples/ted_en_zh/st1
)
|
## Text-to-Speech Models
...
...
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