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Found 6 papers, 0 papers with code
Towards a World-English Language Model for On-Device Virtual Assistants
Based on this insight and leveraging the design of our production models, we introduce a new architecture for World English NNLM that meets the accuracy, latency, and memory constraints of our single-dialect models.
Cross-lingual Knowledge Transfer and Iterative Pseudo-labeling for Low-Resource Speech Recognition with Transducers
Voice technology has become ubiquitous recently.
Training Large-Vocabulary Neural Language Models by Private Federated Learning for Resource-Constrained Devices
Our goal is to train a large neural network language model (NNLM) on compute-constrained devices while preserving privacy using FL and DP.
Accelerating Sparse Matrix Operations in Neural Networks on Graphics Processing Units
Operations using sparse structures are common in natural language models at the input and output layers, because these models operate on sequences over discrete alphabets.
Composing Finite State Transducers on GPUs
Weighted finite-state transducers (FSTs) are frequently used in language processing to handle tasks such as part-of-speech tagging and speech recognition.
Decoding with Finite-State Transducers on GPUs
Weighted finite automata and transducers (including hidden Markov models and conditional random fields) are widely used in natural language processing (NLP) to perform tasks such as morphological analysis, part-of-speech tagging, chunking, named entity recognition, speech recognition, and others.
