From 5de9e75d587b752d8d1063cc7903c4571df99189 Mon Sep 17 00:00:00 2001
From: yhliang <68215459+yhliang-aslp@users.noreply.github.com>
Date: 星期四, 20 四月 2023 16:52:47 +0800
Subject: [PATCH] Merge pull request #389 from alibaba-damo-academy/main
---
egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md | 26 +++++++++++++++++++++-----
1 files changed, 21 insertions(+), 5 deletions(-)
diff --git a/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md b/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md
index 79cc3c3..c740f71 100644
--- a/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md
+++ b/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md
@@ -23,21 +23,37 @@
- Setting parameters in `infer.sh`
- <strong>model:</strong> # model name on ModelScope
- - <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed
+ - <strong>data_dir:</strong> # the dataset dir needs to include `${data_dir}/wav.scp`. If `${data_dir}/text` is also exists, CER will be computed
- <strong>output_dir:</strong> # result dir
- <strong>batch_size:</strong> # batchsize of inference
- <strong>gpu_inference:</strong> # whether to perform gpu decoding, set false for cpu decoding
- <strong>gpuid_list:</strong> # set gpus, e.g., gpuid_list="0,1"
- <strong>njob:</strong> # the number of jobs for CPU decoding, if `gpu_inference`=false, use CPU decoding, please set `njob`
-- Then you can run the pipeline to infer with:
-```python
- sh infer.sh
+- Decode with multi GPUs:
+```shell
+ bash infer.sh \
+ --model "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" \
+ --data_dir "./data/test" \
+ --output_dir "./results" \
+ --batch_size 64 \
+ --gpu_inference true \
+ --gpuid_list "0,1"
+```
+
+- Decode with multi-thread CPUs:
+```shell
+ bash infer.sh \
+ --model "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" \
+ --data_dir "./data/test" \
+ --output_dir "./results" \
+ --gpu_inference false \
+ --njob 64
```
- Results
-The decoding results can be found in `$output_dir/1best_recog/text.cer`, which includes recognition results of each sample and the CER metric of the whole test set.
+The decoding results can be found in `${output_dir}/1best_recog/text.cer`, which includes recognition results of each sample and the CER metric of the whole test set.
If you decode the SpeechIO test sets, you can use textnorm with `stage`=3, and `DETAILS.txt`, `RESULTS.txt` record the results and CER after text normalization.
--
Gitblit v1.9.1