Syllable or phoneme spotting if reliably achieved, provides a good solution to the spoken word andlor continuous speech recognition problem, . We previously showed tha t the Time-Delay Neural Network (TDNN) provided excellent recognition performance (98.6%) of the "BDG" consonant task. We would also like to extend the encouraging performance of TDNN to wordlcontinuous speech recognition. In thi...

The paper proposes a general version of a coupled Hidden Markov/Bayesian Network model for performing phoneme recognition on acoustic-articulatory data. The model uses knowledge learned from the articulatory measurements, available for training, for phoneme recognition on the acoustic input. After training on the articulatory data, the model is able to predict 71.5% of the articulatory state se...

Recognition of second language speech is still a challenging task even for state-of-the-art automatic speech recognition (ASR) systems. Considering that second language speech usually includes less fluent pronunciation and mispronunciation even when it is grammatically correct, we propose a novel phonetic decision tree (PDT) method considering integrated acoustic and linguistic features to deri...

In this paper we present a speech recognition system based on articulatory dynamics. We do not extend the acoustic feature with any explicit articulatory measurements but instead the articulatory dynamics of speech are structurally embodied within episodic memories. The proposed recognizer is made of different memories each specialized for a particular articulator. As all the articulators do no...

Models of speech recognition (by both human and machine) have traditionally assumed the phoneme to serve as the fundamental unit of phonetic and phonological analysis. However, phoneme-centric models have failed to provide a convincing theoretical account of the process by which the brain extracts meaning from the speech signal and have fared poorly in automatic recognition of natural, informal...

In this paper, two techniques are proposed to enhance the nonnative (Japanese English) speech recognition performance. The first technique effectively integrates orthographic representation of a phoneme as an additional context in state clustering in training tied-state triphones. Non-native speakers often learned the target language not through their ears but through their eyes and it is easil...

In the present work we study the applicability of Support Vector Machines (SVMs) on the phoneme recognition task. Specifically, the Least Squares version of the algorithm (LS-SVM) is employed in recognition of the Greek phonemes in the framework of telephone-driven voice-enabled information service. The N-best candidate phonemes are identified and consequently feed to the speech and language re...

This paper proposes a phoneme lattice based TextTiling approach towards multilingual story segmentation. The phoneme is the smallest segmental unit in a language and the number of phonemes in a language is usually far smaller than the number of words. Furthermore, many phonemes are shared by different languages. These properties make phonemes particularly appropriate for representing multilingu...