nvidia-riva · NikhilSrihari · May 26, 2022 · Apr 29, 2022 · Apr 29, 2022 · May 3, 2022
diff --git a/New-language-adaptation/German/README.md b/New-language-adaptation/German/README.md
@@ -1,4 +1,4 @@
-<img src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png" style="width: 90px; float: right;">
+<img src="http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_asr_new-language-adaptation-german-readme/nvidia_logo.png" style="width: 90px; float: right;">
 
 # The Making of RIVA German ASR Service
 

diff --git a/New-language-adaptation/Hindi/README.md b/New-language-adaptation/Hindi/README.md
@@ -1,4 +1,4 @@
-<img src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png" style="width: 90px; float: right;">
+<img src="http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_asr_new-language-adaptation-hindi-readme/nvidia_logo.png" style="width: 90px; float: right;">
 
 # The Making of RIVA Hindi ASR Service
 

diff --git a/New-language-adaptation/Mandarin/README.md b/New-language-adaptation/Mandarin/README.md
@@ -1,5 +1,5 @@
 
-<img src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png" style="width: 90px; float: right;">
+<img src="http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_asr_new-language-adaptation-mandarin-readme/nvidia_logo.png" style="width: 90px; float: right;">
 
 # The Making of the Riva Mandarin ASR Service
 
@@ -33,7 +33,7 @@ Proprietary datasets:
 - 4 speech datasets: 1018 hours.
 - 3 speech datasets: 510 hours.
 
-In total, we have 2707 hours of Mandarin speech audio data.
+In total, we have 2707 hours (320GB) of Mandarin speech audio data.
 
 ## 2. Data preparation
 

diff --git a/README.md b/README.md
@@ -1,3 +1,5 @@
+<img src="http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_all_tutorials-readme/nvidia_logo.png" style="width: 90px; float: right;">
+
 # Riva Speech Skills Tutorials
 
 The best way to get started with Riva is to start with the tutorials.

diff --git a/asr-how-to-improve-recognition-for-specific-words.md b/asr-how-to-improve-recognition-for-specific-words.md
@@ -1,4 +1,4 @@
-<img src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png" style="width: 90px; float: right;">
+<img src="http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_asr_asr-how-to-improve-recognition-for-specific-words/nvidia_logo.png" style="width: 90px; float: right;">
 
 # How to Improve Recognition of Specific Words
 

diff --git a/asr-python-advanced-customize-vocabulary-and-lexicon.ipynb b/asr-python-advanced-customize-vocabulary-and-lexicon.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_asr_asr-python-advanced-customize-vocabulary-and-lexicon/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
     "\n",
     "# How to Customize Riva ASR Vocabulary and Pronunciation with Lexicon Mapping\n",
     "\n",

diff --git a/asr-python-advanced-finetune-am-citrinet-for-noisy-audio-withtao.ipynb b/asr-python-advanced-finetune-am-citrinet-for-noisy-audio-withtao.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_asr_asr-python-advanced-finetune-am-citrinet-for-noisy-audio-withtao/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
     "\n",
     "# How to improve accuracy on specific speech patterns by fine-tuning the Acoustic Model (Citrinet) in the Riva ASR pipeline \n",
     "\n",

diff --git a/asr-python-advanced-finetune-am-citrinet-tao-deployment.ipynb b/asr-python-advanced-finetune-am-citrinet-tao-deployment.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_asr_asr-python-advanced-finetune-am-citrinet-tao-deployment/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
     "\n",
     "# How to deploy custom Acoustic Model (Citrinet) trained with TAO Toolkit on Riva\n",
     "This tutorial walks you through the deployment of custom acoustic model (Citrinet) trained with TAO Toolkit on Riva."

diff --git a/asr-python-advanced-finetune-am-citrinet-tao-finetuning.ipynb b/asr-python-advanced-finetune-am-citrinet-tao-finetuning.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_asr_asr-python-advanced-finetune-am-citrinet-tao-finetuning/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
     "\n",
     "# How to fine-tune a Riva ASR Acoustic Model (Citrinet) with TAO Toolkit\n",
     "This tutorial walks you through how to fine-tune a Riva ASR acoustic model (Citrinet) with TAO Toolkit."
@@ -651,7 +651,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In this section, we are going to run inference on the tlt checkpoint with TAO Toolkit. \n For real-time inference and best latency, we need to deploy this model on Riva - Refer to [How to deploy custom Acoustic Model (Citrinet) trained with TAO Toolkit on Riva](https://github.com/nvidia-riva/tutorials/blob/dev/22.04-citrinet/asr-python-advanced-finetune-am-citrinet-tao-deployment.ipynb) tutorial. \n You might have to work with the infer.yaml file to select the files you want for inference."
+    "In this section, we are going to run inference on the tlt checkpoint with TAO Toolkit. \n",
+    " For real-time inference and best latency, we need to deploy this model on Riva - Refer to [How to deploy custom Acoustic Model (Citrinet) trained with TAO Toolkit on Riva](https://github.com/nvidia-riva/tutorials/blob/dev/22.04-citrinet/asr-python-advanced-finetune-am-citrinet-tao-deployment.ipynb) tutorial. \n",
+    " You might have to work with the infer.yaml file to select the files you want for inference."
    ]
   },
   {

diff --git a/asr-python-advanced-tao-ngram-pretrain.ipynb b/asr-python-advanced-tao-ngram-pretrain.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_asr_asr-python-advanced-tao-ngram-pretrain/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
     "\n",
     "# How to pretrain a Riva ASR Language Modeling (n-gram) with TAO Toolkit\n",
     "This tutorial walks you through the pretraining of Riva ASR language modeling (n-gram) with Train Adapt Optimize (TAO) Toolkit."
@@ -96,7 +96,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-  "### Installing and setting up TAO\n",
+    "### Installing and setting up TAO\n",
     "Install TAO Toolkit inside a Python virtual environment. We recommend performing this step first and then launching the tutorial from the virtual environment.\n",
     "\n",
     "It's a simple `pip` install."

diff --git a/asr-python-advanced-wordboosting.ipynb b/asr-python-advanced-wordboosting.ipynb
@@ -5,7 +5,7 @@
    "id": "2bf1191b",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_asr_asr-python-advanced-wordboosting/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
     "\n",
     "# How do I boost specific words at runtime with word boosting?\n",
     "\n",

diff --git a/asr-python-basics.ipynb b/asr-python-basics.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_asr_asr-python-basics/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
     "\n",
     "# How do I use Riva ASR APIs with out-of-the-box models?\n",
     "\n",

diff --git a/deploy-eks.md b/deploy-eks.md
@@ -1,3 +1,5 @@
+<img src="http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_asr_deploy-eks/nvidia_logo.png" style="width: 90px; float: right;">
+
 # How to Deploy Riva at Scale on AWS with EKS
 
 This is an example of deploying and scaling Riva Speech Skills on Amazon Web Services (AWS) Elastic Kubernetes Service (EKS)

diff --git a/tts-python-advanced-customization-with-ssml.ipynb b/tts-python-advanced-customization-with-ssml.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_tts_tts-python-advanced-customization-with-ssml/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
     "\n",
     "# How do I customize Riva TTS audio output with SSML?\n",
     "\n",

diff --git a/tts-python-advanced-pretrain-tts-tao-deployment.ipynb b/tts-python-advanced-pretrain-tts-tao-deployment.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_tts_tts-python-advanced-pretrain-tts-tao-deployment/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
     "\n",
     "# How to Deploy a custom TTS Models (FastPitch and HiFi-GAN) trained with TAO Toolkit Riva"
    ]

diff --git a/tts-python-advanced-pretrain-tts-tao-training.ipynb b/tts-python-advanced-pretrain-tts-tao-training.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_tts_tts-python-advanced-pretrain-tts-tao-training/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
     "\n",
     "# How to train Riva TTS models (FastPitch and HiFiGAN) with TAO Toolkit"
    ]

diff --git a/tts-python-basics.ipynb b/tts-python-basics.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/riva_tts_tts-python-basics/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
     "\n",
     "# How do I use Riva TTS APIs with out-of-the-box models?\n",
     "\n",