Learning linearly separable features for speech recognition using convolutional neural networks

no code implementations • 22 Dec 2014 • Dimitri Palaz, Mathew Magimai. -Doss, Ronan Collobert

This system was shown to yield similar or better performance than HMM/ANN based system on phoneme recognition task and on large scale continuous speech recognition task, using less parameters.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

End-to-end Phoneme Sequence Recognition using Convolutional Neural Networks

1 code implementation • 7 Dec 2013 • Dimitri Palaz, Ronan Collobert, Mathew Magimai. -Doss

Most phoneme recognition state-of-the-art systems rely on a classical neural network classifiers, fed with highly tuned features, such as MFCC or PLP features.

Estimating Phoneme Class Conditional Probabilities from Raw Speech Signal using Convolutional Neural Networks

no code implementations • 3 Apr 2013 • Dimitri Palaz, Ronan Collobert, Mathew Magimai. -Doss

Motivated from these studies, in the framework of convolutional neural networks (CNNs), this paper investigates a novel approach, where the input to the ANN is raw speech signal and the output is phoneme class conditional probability estimates.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1