this paper introduces a novel approach to improve performance of speech recognition systems using a combination of features obtained from speech reconstructed phase space (rps) and frequency domain analysis. by choosing an appropriate value for the dimension, reconstructed phase space is assured to be topologically equivalent to the dynamics of the speech production system, and could therefore ...

Speech recognition has gradually improved over the years, phoneme recognition in particular. Phoneme recognition plays very important role in speech processing. Phoneme strings are basic representation for automatic language recognition and it is proved that language recognition results are highly correlated with phoneme recognition results. Nowadays, many recognizers are based on Artificial ne...

Introduction: This research was planned to determine some verbal-auditory skills (verbal-auditory short memory and phonological awareness) that have the closest relationship with speech and language development in 5-year-old children. Method: In this descriptive cross-sectional study, 400 children of pre-school classes affiliated to Education and Welfare organizations in Semnan city were select...

In this report, we show that Out-Of-Vocabulary items (OOVs), recognized using phoneme recognition, can be reasonably reliably transcribed orthographically using Machine Learning techniques. More specifically, (i) we show baseline performance of a machine learning approach to phoneme-to-grapheme conversion when different levels of artificial noise are added (simulating phoneme recognizer errors)...

The phoneme classification inaccuracy at the acoustic phonetic level is a major weakness in most speech recognition systems. However, the inaccuracy will violate phonotactic constraints at the acoustic phonetic level. A better performance is expected if a language model is adopted in a recognition system for post-processing phoneme estimates and making corrections with a set of explicit rules o...

Speech sounds can be characterized by articulatory features. Articulatory features are typically estimated using a set of multilayer perceptrons (MLPs), i.e., a separate MLP is trained for each articulatory feature. In this paper, we investigate multitask learning (MTL) approach for joint estimation of articulatory features with and without phoneme classification as subtask. Our studies show th...

In this paper, we analyze the confusions patterns at three places in the hybrid phoneme recognition system. The confusions are analyzed at the pronunciation, the posterior probability, and the phoneme recognizer levels. The confusions show significant structure that is similar at all levels. Some confusions also correlate with human psychoacoustic experiments in white masking noise. These struc...

This paper presents a simple speech recognition system using Gaussian mixtures as phoneme models. The proposed architecture does not follow the integrated search strategy. Instead we use a modular design. We propose two modifications to the Viterbi decoding algorithm in order to be applicable to our phoneme models. Both strategies have been implemented and tested on two corpora. Experiments hav...

In this paper a phoneme recognition system based on predictive neural networks is proposed. Neural networks are used to predict observation vectors of speech frames. The obtained prediction error is used for phoneme recognition as 1) distortion measure on the frame level and 2) as feature, which is statistically modeled by the Rayleigh distribution. Continuous speech phoneme recognition experim...