Empirical comparison of two multilayer perceptron-based keyword speech recognition algorithms

Wordspotting using a predictive neural model for the telephone speech corpus

We describe a wordspotting algorithm based on a predictive neural model for a telephone speech corpus. Each keyword is modeled as a whole word. For keyword detection scoring we used a minimum accumulated prediction residual. We computed empirically a threshold value for rejecting non-keyword speech in place of building non-keyword models. We tested the algorithm with the TUBTEL telephone speech...

Improved Bottleneck Feature using Hierarchical Deep Belief Networks for Keyword Spotting in Continues Speech

Bottleneck (BN) feature has attracted considerable attentions by its capacity of improving the accuracies in speech recognition tasks. Recently, researchers have proposed some modified approaches for extracting more effective BN feature, but these approaches still need further improvement. In this paper, motivated by both deep belief networks (DBN) and hierarchical Multilayer Perceptron (MLP), ...

K Eyword S Potting on W Ord L Attices

In spite of its numerous potential applications, Automatic Speech Recognition (ASR) remains a difficult (and mainly unsolved) problem. In addition to the intrinsic difficulty of the task, users tend to go beyond the pre-defined lexicon words, and the important keywords necessary to understand voice requests are often lost in extra words. In this context, it is often interesting to develop Keywo...

Multilayer Perceptron Based Hierarchical Acoustic Modeling for Automatic Speech Recognition

A Comparison of the Lbg, Lvq, Mlp, Som and Gmm Algorithms for Vector Quantisation and Clustering Analysis

We compare the performance of ve algorithms for vector quan-tisation and clustering analysis: the Self-Organising Map (SOM) and Learning Vector Quantization (LVQ) algorithms of Kohonen, the Linde-Buzo-Gray (LBG) algorithm, the MultiLayer Perceptron (MLP) and the GMM/EM algorithm for Gaussian Mixture Models (GMM). We propose that the GMM/EM provides a better representation of the speech space an...