Multilayer neural networks trained with the back-propagation algorithm constitute the best
example of a successful gradient based learning technique. Given an appropriate network …

Abstract Energy-Based Models (EBMs) capture dependencies between variables by
associating a scalar energy to each configuration of the variables. Inference consists in …

We describe an online handwriting system that is able to support 102 languages using a
deep neural network architecture. This new system has completely replaced our previous …

Connectionist Speech Recognition: A Hybrid Approach describes the theory and
implementation of a method to incorporate neural network approaches into state of the art …

This thesis examines how artificial neural networks can benefit a large vocabulary, speaker
independent, continuous speech recognition system. Currently, most speech recognition …

The authors are concerned with integrating connectionist networks into a hidden Markov
model (HMM) speech recognition system. This is achieved through a statistical interpretation …

Abstract Hidden Markov Models (HMMs) are statistical models of sequential data that have
been used successfully in many applications, especially for speech recognition. We rst …

Time-aligned lyrics can enrich the music listening experience by enabling karaoke, text-
based song retrieval and intra-song navigation, and other applications. Compared to text-to …

In spite of the advances accomplished throughout the last decades, automatic speech
recognition (ASR) is still a challenging and difficult task. In particular, recognition systems …

In this paper an original method for integrating Arti cial Neural Networks (ANN) with Hidden
Markov Models (HMM) is proposed. ANNs are suitable to perform phonetic classi cation …