diff --git a/tutorials/tools/CTC_Segmentation_Tutorial.ipynb b/tutorials/tools/CTC_Segmentation_Tutorial.ipynb
index 84a5db7e8768..fd156c030d26 100644
--- a/tutorials/tools/CTC_Segmentation_Tutorial.ipynb
+++ b/tutorials/tools/CTC_Segmentation_Tutorial.ipynb
@@ -1,39 +1,12 @@
 {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
-    "accelerator": "GPU",
-    "colab": {
-      "name": "CTC_Segmentation_Tutorial_update.ipynb",
-      "private_outputs": true,
-      "provenance": [],
-      "collapsed_sections": [],
-      "toc_visible": true
-    },
-    "kernelspec": {
-      "display_name": "Python 3 (ipykernel)",
-      "language": "python",
-      "name": "python3"
-    },
-    "language_info": {
-      "codemirror_mode": {
-        "name": "ipython",
-        "version": 3
-      },
-      "file_extension": ".py",
-      "mimetype": "text/x-python",
-      "name": "python",
-      "nbconvert_exporter": "python",
-      "pygments_lexer": "ipython3",
-      "version": "3.9.7"
-    }
-  },
   "cells": [
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "d4KCUoxSpdoZ"
       },
+      "outputs": [],
       "source": [
         "BRANCH = 'r2.1.0'\n",
         "\n",
@@ -46,15 +19,15 @@
         "3. Connect to an instance with a GPU (Runtime -> Change runtime type -> select \"GPU\" for hardware accelerator)\n",
         "4. Run this cell to set up dependencies.\n",
         "\"\"\""
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "JDk9zxC6pdod"
       },
+      "outputs": [],
       "source": [
         "import os\n",
         "# either provide a path to local NeMo repository with NeMo already installed or git clone\n",
@@ -67,15 +40,15 @@
         "  ! git clone -b $BRANCH https://github.com/NVIDIA/NeMo\n",
         "  ! cd NeMo\n",
         "  ! python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "CH7yR7cSwPKr"
       },
+      "outputs": [],
       "source": [
         "import json\n",
         "import os\n",
@@ -88,9 +61,7 @@
         "! pip install pandas\n",
         "! pip install plotly\n",
         "from plotly import graph_objects as go"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -108,17 +79,18 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "8FAZKakrIyGI"
       },
+      "outputs": [],
       "source": [
         "requirements = f'https://raw.githubusercontent.com/NVIDIA/NeMo/{BRANCH}/tools/ctc_segmentation/requirements.txt'\n",
         "wget.download(requirements)\n",
         "! pip install -r requirements.txt\n",
-        "! apt-get install -y ffmpeg"
-      ],
-      "execution_count": null,
-      "outputs": []
+        "! apt-get install -y ffmpeg\n",
+        "! apt-get install -y libsox-fmt-mp3 "
+      ]
     },
     {
       "cell_type": "markdown",
@@ -131,9 +103,11 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "1C9DdMfvRFM-"
       },
+      "outputs": [],
       "source": [
         "if 'google.colab' in str(get_ipython()):\n",
         "  NEMO_DIR_PATH = \"/content/NeMo\"\n",
@@ -143,9 +117,7 @@
         "TOOLS_DIR = f'{NEMO_DIR_PATH}/tools/ctc_segmentation/scripts'\n",
         "print(TOOLS_DIR)\n",
         "! ls -l $TOOLS_DIR"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -159,9 +131,11 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "bkeKX2I_tIgV"
       },
+      "outputs": [],
       "source": [
         "## create data directory and download an audio file\n",
         "WORK_DIR = 'WORK_DIR'\n",
@@ -174,9 +148,7 @@
         "! rm $DATA_DIR/audio_samples.zip\n",
         "\n",
         "DATA_DIR = os.path.join(DATA_DIR, \"audio_samples\")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -189,14 +161,14 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "Y6VYVk9mpdol"
       },
+      "outputs": [],
       "source": [
         "! ls $DATA_DIR"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -209,14 +181,14 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "IGhijb-Bpdol"
       },
+      "outputs": [],
       "source": [
         "! ls $DATA_DIR/es/audio/ $DATA_DIR/es/text/"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -231,15 +203,15 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "ulkPrqwipdom"
       },
+      "outputs": [],
       "source": [
         "base_name_es = \"el19demarzoyel2demayo_03_perezgaldos\"\n",
         "Audio(f\"{DATA_DIR}/es/audio/{base_name_es}.wav\")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -252,15 +224,15 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "9Qfp10Xnpdom"
       },
+      "outputs": [],
       "source": [
         "text = f\"{DATA_DIR}/es/text/{base_name_es}.txt\"\n",
         "! cat $text"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -296,9 +268,11 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "u4zjeVVv-UXR"
       },
+      "outputs": [],
       "source": [
         "MODEL = \"stt_es_citrinet_512\" \n",
         "OUTPUT_DIR = WORK_DIR + \"/es_output\"\n",
@@ -311,9 +285,7 @@
         "--language='en' \\\n",
         "--model=$MODEL \\\n",
         "--audio_dir=$DATA_DIR/es/audio"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -331,14 +303,14 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "6R7OKAsYH9p0"
       },
+      "outputs": [],
       "source": [
         "! ls $OUTPUT_DIR/processed"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -351,14 +323,14 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "74GLpMgoICmk"
       },
+      "outputs": [],
       "source": [
         "! head $OUTPUT_DIR/processed/el19demarzoyel2demayo_03_perezgaldos.txt"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -376,9 +348,11 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "xyKtaqAd-Tvk"
       },
+      "outputs": [],
       "source": [
         "WINDOW = 8000\n",
         "\n",
@@ -387,9 +361,7 @@
         "--data=$OUTPUT_DIR/processed \\\n",
         "--model=$MODEL \\\n",
         "--window_len=$WINDOW "
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -404,15 +376,15 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "ktBAsfJRVCwI"
       },
+      "outputs": [],
       "source": [
         "alignment_file = f\"{WINDOW}_{base_name_es}_segments.txt\"\n",
         "! head -n 3 $OUTPUT_DIR/segments/$alignment_file"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -451,9 +423,11 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "6YM64RPlitPL"
       },
+      "outputs": [],
       "source": [
         "OFFSET = 0\n",
         "THRESHOLD = -2\n",
@@ -463,9 +437,7 @@
         "--alignment=$OUTPUT_DIR/segments/ \\\n",
         "--threshold=$THRESHOLD \\\n",
         "--offset=$OFFSET"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -480,9 +452,11 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "1UaSIflBZwaV"
       },
+      "outputs": [],
       "source": [
         "wget.download(f'https://raw.githubusercontent.com/NVIDIA/NeMo/{BRANCH}/examples/asr/transcribe_speech.py')\n",
         "\n",
@@ -490,15 +464,15 @@
         "pretrained_name=$MODEL \\\n",
         "dataset_manifest=$OUTPUT_DIR/manifests/manifest.json \\\n",
         "output_filename=$OUTPUT_DIR/manifests/manifest_transcribed.json"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "F-nPT8z_IVD-"
       },
+      "outputs": [],
       "source": [
         "def plot_signal(signal, sample_rate):\n",
         "    \"\"\" Plot the signal in time domain \"\"\"\n",
@@ -530,9 +504,7 @@
         "                display('ASR transcript: ' + sample['pred_text'])\n",
         "            print(f\"Score: {sample['score']}\")\n",
         "            print('\\n' + '-' * 110)"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -549,17 +521,17 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "Q45uBtsHIaAD"
       },
+      "outputs": [],
       "source": [
         "# let's examine only a few first samples\n",
         "! head -n 2 $OUTPUT_DIR/manifests/manifest_transcribed.json > $OUTPUT_DIR/manifests/samples.json\n",
         "\n",
         "display_samples(f\"{OUTPUT_DIR}/manifests/samples.json\")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -576,14 +548,14 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "KRc9yMjPXPgj"
       },
+      "outputs": [],
       "source": [
         "! ls $DATA_DIR/en/audio $DATA_DIR/en/text"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -626,9 +598,11 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "hRFAl0gO92bp"
       },
+      "outputs": [],
       "source": [
         "MODEL = \"QuartzNet15x5Base-En\" # \"stt_en_citrinet_512_gamma_0_25\" \n",
         "OUTPUT_DIR_2 = WORK_DIR + \"/en_output\"\n",
@@ -642,9 +616,7 @@
         "--SCRIPTS_DIR=$TOOLS_DIR \\\n",
         "--MIN_SCORE=$THRESHOLD  \\\n",
         "--USE_NEMO_NORMALIZATION=False"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -664,32 +636,32 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "xsm89hYlpdor"
       },
+      "outputs": [],
       "source": [
         "! bash $TOOLS_DIR/../run_filter.sh \\\n",
         "--SCRIPTS_DIR=$TOOLS_DIR \\\n",
         "--MODEL_NAME_OR_PATH=stt_en_conformer_ctc_large \\\n",
         "--MANIFEST=$OUTPUT_DIR_2/manifests/manifest.json \\\n",
         "--INPUT_AUDIO_DIR=$DATA_DIR/en/audio/"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": null,
       "metadata": {
         "id": "nacE_iQ2_85L"
       },
+      "outputs": [],
       "source": [
         "# let's examine only a few first samples\n",
         "! head -n 2 $OUTPUT_DIR_2/manifests/manifest_transcribed_metrics_filtered.json > $OUTPUT_DIR_2/manifests/samples.json\n",
         "\n",
         "display_samples(f\"{OUTPUT_DIR_2}/manifests/samples.json\")"
-      ],
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -713,5 +685,34 @@
         "Kürzinger, Ludwig, et al. [\"CTC-Segmentation of Large Corpora for German End-to-End Speech Recognition.\"](https://arxiv.org/abs/2007.09127) International Conference on Speech and Computer. Springer, Cham, 2020."
       ]
     }
-  ]
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "collapsed_sections": [],
+      "name": "CTC_Segmentation_Tutorial_update.ipynb",
+      "private_outputs": true,
+      "provenance": [],
+      "toc_visible": true
+    },
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.9.7"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
 }