NeMo: a toolkit for building AI applications using Neural Modules
원문 초록
NeMo (Neural Modules) is a Python framework-agnostic toolkit for creating AI applications through re-usability, abstraction, and composition. NeMo is built around neural modules, conceptual blocks of neural networks that take typed inputs and produce typed outputs. Such modules typically represent data layers, encoders, decoders, language models, loss functions, or methods of combining activations. NeMo makes it easy to combine and re-use these building blocks while providing a level of semantic correctness checking via its neural type system. The toolkit comes with extendable collections of pre-built modules for automatic speech recognition and natural language processing. Furthermore, NeMo provides built-in support for distributed training and mixed precision on latest NVIDIA GPUs. NeMo is open-source https://github.com/NVIDIA/NeMo
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Addressing Pitfalls in Auditing Practices of Automatic Speech Recognition Technologies: A Case Study of People with Aphasia
Unsupervised Rhythm and Voice Conversion to Improve ASR on Dysarthric Speech
Towards Temporally Explainable Dysarthric Speech Clarity Assessment
Vedavani: A Benchmark Corpus for ASR on Vedic Sanskrit Poetry
BeaverTalk: Oregon State University's IWSLT 2025 Simultaneous Speech Translation System
Exploring Generative Error Correction for Dysarthric Speech Recognition
토론
이 논문과 연결된 포럼 글이 아직 없습니다.