msb-public
/
PaddleSpeech
mirror of https://github.com/PaddlePaddle/PaddleSpeech
1
0
Code Issues Projects Releases Wiki Activity

Update experimental results for DS2.

Browse Source
pull/2/head
Xinghai Sun 7 years ago
parent f4e9a9224e
commit 285972e36e
1 changed files with 8 additions and 17 deletions
Show Stats Download Patch File Download Diff File

25
README.md
Unescape View File

@ -426,7 +426,7 @@ python deploy/demo_client.py --help
Language | Model Name | Training Data | Training Hours Language | Model Name | Training Data | Training Hours
:-----------: | :------------: | :----------: | -------: :-----------: | :------------: | :----------: | -------:
English | [LibriSpeech Model](http://cloud.dlnel.org/filepub/?uuid=17404caf-cf19-492f-9707-1fad07c19aae) | [LibriSpeech Dataset](http://www.openslr.org/12/) | 960 h English | [LibriSpeech Model](http://cloud.dlnel.org/filepub/?uuid=17404caf-cf19-492f-9707-1fad07c19aae) | [LibriSpeech Dataset](http://www.openslr.org/12/) | 960 h
English | [Internal English Model](to-be-added) | Baidu English Dataset | 8000 h English | [Internal English Model](to-be-added) | Baidu English Dataset | 8628 h
Mandarin | [Aishell Model](http://cloud.dlnel.org/filepub/?uuid=6c83b9d8-3255-4adf-9726-0fe0be3d0274) | [Aishell Dataset](http://www.openslr.org/33/) | 151 h Mandarin | [Aishell Model](http://cloud.dlnel.org/filepub/?uuid=6c83b9d8-3255-4adf-9726-0fe0be3d0274) | [Aishell Dataset](http://www.openslr.org/33/) | 151 h
Mandarin | [Internal Mandarin Model](to-be-added) | Baidu Mandarin Dataset | 2917 h Mandarin | [Internal Mandarin Model](to-be-added) | Baidu Mandarin Dataset | 2917 h
@ -434,30 +434,21 @@ Mandarin | [Internal Mandarin Model](to-be-added) | Baidu Mandarin Dataset | 291
Language Model | Training Data | Token-based | Size | Filter Configuraiton Language Model | Training Data | Token-based | Size | Filter Configuraiton
:-------------:| :------------:| :-----: | -----: | -----------------: :-------------:| :------------:| :-----: | -----: | -----------------:
[English LM (Median)](http://paddlepaddle.bj.bcebos.com/model_zoo/speech/common_crawl_00.prune01111.trie.klm) | To Be Added | Word-based | 8.3 GB | To Be Added [English LM](http://paddlepaddle.bj.bcebos.com/model_zoo/speech/common_crawl_00.prune01111.trie.klm) | To Be Added | Word-based | 8.3 GB | To Be Added
[English LM (Big)](to-be-added) | To Be Added | Word-based | X.X GB | To Be Added [Mandarin LM](http://cloud.dlnel.org/filepub/?uuid=d21861e4-4ed6-45bb-ad8e-ae417a43195e) | To Be Added | Character-based | 2.8 GB | To Be Added
[Mandarin LM (Median)](http://cloud.dlnel.org/filepub/?uuid=d21861e4-4ed6-45bb-ad8e-ae417a43195e) | To Be Added | Character-based | 2.8 GB | To Be Added
[Mandarin LM (Big)](to-be-added) | To Be Added | Character-based | X.X GB | To Be Added
## Experiments and Benchmarks ## Experiments and Benchmarks
#### English Model Evaluation (Word Error Rate) #### English Model Evaluation (Word Error Rate)
Test Set | LibriSpeech Model | Internal English Model Test Set | LibriSpeech Model | Internal English Model
:---------------------: | :---------------: | :-------------------: :---------------------: | ---------------: | -------------------:
LibriSpeech-Test-Clean | 7.9 | X.X LibriSpeech-Test-Clean | 7.96 | X.X
LibriSpeech-Test-Other | X.X | X.X LibriSpeech-Test-Other | 23.87 | X.X
VoxForge-Test | X.X | X.X VoxForge-Test | X.X | X.X
Baidu-English-Test | X.X | X.X Baidu-English-Test | X.X | X.X
#### English Model Evaluation (Character Error Rate) (Beam size=2000)
Test Set | LibriSpeech Model | Internal English Model
:---------------------: | :---------------: | :-------------------:
LibriSpeech-Test-Clean | X.X | X.X
LibriSpeech-Test-Other | X.X | X.X
VoxForge-Test | X.X | X.X
Baidu-English-Test | X.X | X.X
#### Mandarin Model Evaluation (Character Error Rate) #### Mandarin Model Evaluation (Character Error Rate)
@ -468,7 +459,7 @@ Baidu-Mandarin-Test | X.X | X.X
#### Acceleration with Multi-GPUs #### Acceleration with Multi-GPUs
We compare the training time with 1, 2, 4, 8, 16 Tesla K40m GPUs (with a subset of LibriSpeech samples whose audio durations are between 6.0 and 7.0 seconds). And it shows that a **near-linear** acceleration with multiple GPUs has been achieved. In the following figure, the time (in seconds) used for training is plotted on the blue bars. We compare the training time with 1, 2, 4, 8, 16 Tesla K40m GPUs (with a subset of LibriSpeech samples whose audio durations are between 6.0 and 7.0 seconds). And it shows that a **near-linear** acceleration with multiple GPUs has been achieved. In the following figure, the time (in seconds) cost for training is printed on the blue bars.
<img src="docs/images/multi_gpu_speedup.png" width=450><br/> <img src="docs/images/multi_gpu_speedup.png" width=450><br/>

Write Preview
Loading…
Cancel
Save