NVIDIA NeMo: An Open-Source Toolkit For Developing State-Of-The-Art Conversational AI Models In Three Lines Of Code – MarkTechPost

NVIDIAs open-source toolkit, NVIDIA NeMo( Neural Models), is a revolutionary step towards the advancement of Conversational AI. Based on PyTorch, it allows one to build quickly, train, and fine-tune conversational AI models.

As the world is getting more digital, Conversational AI is a way to enable communication between humans and computers. The set of technologies behind some fascinating technologies like automated messaging, speech recognition, voice chatbots, text to speech, etc. It broadly comprises three areas of AI research: automatic speech recognition (ASR), natural language processing (NLP), and speech synthesis (or text-to-speech, TTS).

Conversational AI has shaped the path of human-computer interaction, making it more accessible and exciting. The latest advancements in Conversational AI like NVIDIA NeMo help bridge the gap between machines and humans.

NVIDIA NeMo consists of two subparts: NeMo Core and NeMo Collections. NeMo Core deals with all models generally, whereas NeMo Collections deals with models specific domains. In Nemos Speech collection (nemo_asr), youll find models and various building blocks for speech recognition, command recognition, speaker identification, speaker verification, and voice activity detection. NeMos NLP collection (nemo_nlp) contains models for tasks such as question answering, punctuation, named entity recognition, and many others. Finally, in NeMos Speech Synthesis (nemo_tts), youll find several spectrogram generators and vocoders, which will let you generate synthetic speech.

There are three main concepts in NeMo: model, neural module, and neural type.

Even though NeMo is based on PyTorch, it can also be effectively used with other projects likePyTorch LightningandHydra. Integration with Lightning makes it easier to train models with mixed precision using Tensor Cores and can scale training to multiple GPUs and compute nodes. It also has some features like logging, checkpointing, overfit checking, etc. Hydra also allows the parametrization of scripts to keep it well organized. It makes it easier to streamline everyday tasks for users.

Github: https://github.com/NVIDIA/NeMo#tutorials

Web: https://developer.nvidia.com/nvidia-nemo

Pytorch Blog: https://medium.com/@samfarahzad/nvidia-nemo-neural-modules-and-models-for-conversational-ai-ea041e4cd4

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NVIDIA NeMo: An Open-Source Toolkit For Developing State-Of-The-Art Conversational AI Models In Three Lines Of Code - MarkTechPost