Latent Words Recurrent Neural Network Language Models for Automatic Speech Recognition

IEICE Transactions on Information and Systems - Japan
doi 10.1587/transinf.2018edp7242
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Related search

Recurrent Neural Network Language Model Adaptation for Multi-Genre Broadcast Speech Recognition and Alignment

IEEE/ACM Transactions on Audio Speech and Language Processing
Electronic EngineeringUltrasonicsSignal ProcessingInstrumentationAcousticsMedia TechnologyHearingElectricalComputer ScienceSpeechComputational Mathematics
2019English

Unidirectional Neural Network Architectures for End-To-End Automatic Speech Recognition

2019English

Latent Semantic Information in Maximum Entropy Language Models for Conversational Speech Recognition

2003English

Exploration of the Impact of Maximum Entropy in Recurrent Neural Network Language Models for Code-Switching Speech

2014English

Automatic Speech Recognition With Deep Neural Networks for Impaired Speech

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2016English

Training Methods for Deep Neural Network-Based Acoustic Models in Speech Recognition

English

Phonological Models in Automatic Speech Recognition

2008English

Two Efficient Lattice Rescoring Methods Using Recurrent Neural Network Language Models

IEEE/ACM Transactions on Audio Speech and Language Processing
Electronic EngineeringUltrasonicsSignal ProcessingInstrumentationAcousticsMedia TechnologyHearingElectricalComputer ScienceSpeechComputational Mathematics
2016English

Hierarchical Bayesian Language Models for Conversational Speech Recognition

IEEE Transactions on Audio, Speech, and Language Processing
2010English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy