From f0ee6cf0dca4ac378447f1e2d8184ad6b120cfd5 Mon Sep 17 00:00:00 2001
From: Fangjun Kuang <csukuangfj@gmail.com>
Date: Thu, 12 Aug 2021 10:33:50 +0800
Subject: [PATCH] Minor fixes after review.

---
 README.md                     | 24 ------------------------
 egs/librispeech/ASR/README.md |  6 +++---
 2 files changed, 3 insertions(+), 27 deletions(-)

diff --git a/README.md b/README.md
index 2453a60eb..91c1f67a9 100644
--- a/README.md
+++ b/README.md
@@ -22,30 +22,6 @@ Please refer to [k2's installation documentation][k2-install] to install k2.
 If you have any issues about installing k2, please open an issue at
 <https://github.com/k2-fsa/k2/issues>.
 
-The following shows the minimal commands needed to install k2 from source:
-
-```bash
-mkdir $HOME/open-source
-cd $HOME/open-source
-git clone https://github.com/k2-fsa/k2.git
-cd k2
-mkdir build_release
-cd build_release
-cmake -DCMAKE_BUILD_TYPE=Release ..
-make -j _k2
-export PYTHONPATH=$HOME/open-source/k2/k2/python:$PYTHONPATH
-export PYTHONPATH=$HOME/open-source/k2/build_release/lib:$PYTHONPATH
-```
-
-To check that k2 is installed successfully, please run
-
-```bash
-python3 -m k2.version
-```
-
-It should show the information about the environment in which
-k2 was built.
-
 ### Install lhotse
 
 Please refer to [lhotse's installation documentation][lhotse-install] to install
diff --git a/egs/librispeech/ASR/README.md b/egs/librispeech/ASR/README.md
index 3d3a3b267..30778ed05 100644
--- a/egs/librispeech/ASR/README.md
+++ b/egs/librispeech/ASR/README.md
@@ -20,7 +20,7 @@ please run
 The script `./prepare.sh` prepares features, lexicon, LMs, etc.
 All generated files are saved in the folder `./data`.
 
-HINT: `./prepare.sh` support options `--stage` and `--stop-stage`.
+**HINT:** `./prepare.sh` supports options `--stage` and `--stop-stage`.
 
 ## TDNN-LSTM CTC training
 
@@ -31,7 +31,7 @@ Pre-configured parameters for training and decoding are set in the function
 `get_params()` within `tdnn_lstm_ctc/train.py`
 and `tdnn_lstm_ctc/decode.py`.
 
-Parameters that can be passed from the commandline can be found by
+Parameters that can be passed from the command-line can be found by
 
 ```
 ./tdnn_lstm_ctc/train.py --help
@@ -61,4 +61,4 @@ If you want to decode by averaging checkpoints `epoch-8.pt`,
 
 The folder `conformer-ctc` contains scripts for CTC training
 with conformer models. The steps of running the training and
-decoding are similar as `tdnn_lstm_ctc`.
+decoding are similar to `tdnn_lstm_ctc`.