Multilingual and Code-Switched Automatic Speech Recognition with NVIDIA NeMo
Multilingual and Code-Switched Automatic Speech Recognition with NVIDIA NeMo | NVIDIA Technical Blog
Nvidia NeMo (Neural Modules) is a toolkit developed by Nvidia for building and deploying conversational AI models. It is designed to make it easier for developers to create models for various conversational AI applications such as voice assistants, chatbots, and more.
NeMo is built on top of PyTorch and offers pre-built modules and a set of APIs that make it easy to assemble and fine-tune models for various conversational AI tasks such as text classification, sequence labeling, machine translation, and more. It also provides support for popular conversational AI datasets, such as the SNLI (Stanford Natural Language Inference) corpus, and the MNLI (Multilingual Natural Language Inference) corpus.
In addition to these pre-built modules, NeMo also provides a flexible framework that allows users to build custom models from scratch and integrate them into existing conversational AI applications. This makes it possible for developers to create custom models that are tailored to specific use cases and provide enhanced accuracy and performance.
Overall, Nvidia NeMo provides a comprehensive and user-friendly platform for building and deploying conversational AI models, making it a popular choice for developers in the field.