Combining Mixture Weight Pruning and Quantization for Small-Footprint Speech Recognition

doi 10.1109/icassp.2009.4960552
Full Text
Abstract

Available in full text

Date
Authors
Publisher

IEEE

Related search

The Subspace Gaussian Mixture Model—A Structured Model for Speech Recognition

Computer Speech and Language
Theoretical Computer ScienceHuman-Computer InteractionSoftware
2011English

Combining Acoustic and Electric Stimulation in the Service of Speech Recognition

International Journal of Audiology
LinguisticsSpeechLanguageHearing
2010English

A Robust Method for Speech Emotion Recognition Based on Infinite Student’st-Mixture Model

Mathematical Problems in Engineering
MathematicsEngineering
2015English

On Combining F0 Contour and Vocal Tract Length Normalisation for Speech Recognition of Vietnamese Proper Names

Journal of Computer Science and Cybernetics
2012English

Empirically Combining Unnormalized NNLM and Back-Off N-Gram for Fast N-Best Rescoring in Speech Recognition

Eurasip Journal on Audio, Speech, and Music Processing
AcousticsUltrasonicsElectricalElectronic Engineering
2014English

Big Data Small Footprint

Proceedings of the VLDB Endowment
Computer Science
2014English

Shape Quantization and Recognition With Randomized Trees

Neural Computation
ArtsCognitive NeuroscienceHumanities
1997English

Trainable Grammars for Speech Recognition

Journal of the Acoustical Society of America
AcousticsUltrasonicsArtsHumanities
1979English

Visual Speech Feature Extraction for Improved Speech Recognition

2002English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy