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* [JARS-2115] Add TAO asr-citrinet model to Riva tutorial (#25)

* add initial citrinet model from TAO

* modify the notebook with RIVA introduction

* add tao-citrinet-deploy

* rename citrinet finetune file

* add riva explaination to tao-citrinet-deploy

* add correct citrinet

* citrinet finetune suggestion addressed

* deployment page link updated

* modify tao explain similar to ngram for now

* modify tao explain similar to ngram for now 2

* modify tao explain similar to ngram for now 3

* remove ?

* citrinet deployment add

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* addressed last comments

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* [JARS-2115] Add TAO asr-Ngram model to Riva tutorial (#28)

* initial commit for TAO ngram jupyter file from TAO

* initial commit of ngram TAO

* adapt tao-ngram pretrain to riva

* delete duplicate file

* typo modify

* address comments version1

* address comments 2

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* change modelling --> modeling

* change pre-requisite to installing session

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2 changes: 1 addition & 1 deletion New-language-adaptation/German/README.md
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<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

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2 changes: 1 addition & 1 deletion New-language-adaptation/Hindi/README.md
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<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

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4 changes: 2 additions & 2 deletions New-language-adaptation/Mandarin/README.md
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<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

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- 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

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2 changes: 2 additions & 0 deletions README.md
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<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.
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2 changes: 1 addition & 1 deletion asr-how-to-improve-recognition-for-specific-words.md
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<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

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2 changes: 1 addition & 1 deletion asr-python-advanced-customize-vocabulary-and-lexicon.ipynb
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"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",
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"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",
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"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."
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6 changes: 4 additions & 2 deletions asr-python-advanced-finetune-am-citrinet-tao-finetuning.ipynb
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"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."
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"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."
]
},
{
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4 changes: 2 additions & 2 deletions asr-python-advanced-tao-ngram-pretrain.ipynb
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"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."
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"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."
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2 changes: 1 addition & 1 deletion asr-python-advanced-wordboosting.ipynb
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"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",
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2 changes: 1 addition & 1 deletion asr-python-basics.ipynb
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"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",
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<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)
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2 changes: 1 addition & 1 deletion tts-python-advanced-customization-with-ssml.ipynb
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"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",
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2 changes: 1 addition & 1 deletion tts-python-advanced-pretrain-tts-tao-deployment.ipynb
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"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"
]
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2 changes: 1 addition & 1 deletion tts-python-advanced-pretrain-tts-tao-training.ipynb
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"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"
]
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2 changes: 1 addition & 1 deletion tts-python-basics.ipynb
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"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",
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