From 11faddc83007ab7baacb96cfade00b0bf3689384 Mon Sep 17 00:00:00 2001
From: jinzr <60612200+JinZr@users.noreply.github.com>
Date: Tue, 27 Jun 2023 20:23:33 +0800
Subject: [PATCH] Update RESULTS.md

Lower WERs reported
---
 egs/swbd/ASR/RESULTS.md | 47 +++++++++++++++++++++++++++++++++++++++++
 1 file changed, 47 insertions(+)

diff --git a/egs/swbd/ASR/RESULTS.md b/egs/swbd/ASR/RESULTS.md
index a7c50879b..68a843c01 100644
--- a/egs/swbd/ASR/RESULTS.md
+++ b/egs/swbd/ASR/RESULTS.md
@@ -1,6 +1,53 @@
 ## Results
 ### Switchboard BPE training results (Conformer-CTC)
 
+#### 2023-06-27
+
+The best WER, as of 2023-06-27, for the Switchboard is below
+
+Results using HLG decoding + n-gram LM rescoring + attention decoder rescoring:
+
+|                                |  eval2000  |  rt03  |
+|--------------------------------|------------|--------|
+|         `conformer_ctc`        |    30.80   |  32.29 |
+
+Scale values used in n-gram LM rescoring and attention rescoring for the best WERs are:
+
+##### eval2000
+
+| ngram_lm_scale | attention_scale |
+|----------------|-----------------|
+|      0.9       |       1.1       |
+
+##### rt03
+
+| ngram_lm_scale | attention_scale |
+|----------------|-----------------|
+|      0.9       |       1.9       |
+
+To reproduce the above result, use the following commands for training:
+
+```bash
+cd egs/swbd/ASR
+./prepare.sh
+export CUDA_VISIBLE_DEVICES="0,1"
+./conformer_ctc/train.py \
+  --max-duration 120 \
+  --num-workers 8 \
+  --enable-musan False \
+  --world-size 2 \
+  --num-epochs 100
+```
+
+and the following command for decoding:
+
+```bash
+./conformer_ctc/decode.py \
+  --epoch 99 \
+  --avg 10 \
+  --max-duration 50
+```
+
 #### 2023-06-26
 
 The best WER, as of 2023-06-26, for the Switchboard is below