This study investigated the shortand long-term effects of a high variability perceptual training on the production of three English vowel contrasts (/i//ɪ/; /ɛ/-/æ/; /u/-/ʊ/) by Portuguese learners. The perceptual training consisted of five sessions divided into two blocks that included both discrimination and identification tasks followed by immediate feedback with natural stimuli produced by ...

Character recognition is a field of machine learning that has been under research for several decades. The particular success of neural networks in pattern recognition and therefore character recognition is laudable. Research has also long shown that a single hidden layer network has the capability to approximate any function; while, the problems associated with training deep networks therefore...

The acoustic realization of vowels with lexical stress generally differs substantially from their unstressed counterparts, which are more reduced in spectral quality, shorter in duration, weaker in intensity and tend to have a flatter spectral tilt. Therefore, in a continuous speech recognizer (CSR) it would appear profitable to train separate models for the stressed and unstressed variants of ...

In three experiments, we examined how readers learn and generalize new pronunciations for vowel graphemes. Children ages 6 1/2 to 9 (n = 97) and college students (n = 21) were taught a nonword that included a novel vowel pronunciation in the middle position (e.g., zuop is pronounced /zup/). They were then asked to pronounce other nonwords that contained the same vowel grapheme. Participants wer...

Automatic speech recognition by machine is one of the most efficient methods for man-machine communications. Because speech waveform is nonlinear and variant. Speech recognition requires a lot of intelligence and fault tolerance in the pattern recognition algorithms. Accurate vowel recognition forms the backbone of most successful speech recognition systems. A collection of techniques exists to...

The accuracy with which native Japanese listeners identified American English vowels and coda nasals was assessed before and after training. The listeners were divided into four groups, each of which received a different type of training. Two of the four groups were vowel-oriented; one of these groups received vowel identification training (VI), while the other received vowel discrimination tra...

Computer Assisted Pronunciation Training systems have become popular tools to train on second languages. Many second language learners prefer to train on pronunciation in a stress free environment with no other listeners. There exists no such tool for training on pronunciation of the Norwegian language. Pronunciation exercises in training systems should be directed at important properties in th...

One of the frequent symptoms of Parkinson’s disease (PD) is a progressive dysarthria, the difficulty with articulation. Characterization of dysarthric speech is important, for instance, for the adaptation of speech recognition systems to PD patients. In this work, we investigate acoustic and phonetic-prosodic characteristics of speech produced by PD patients in the European Portuguese. For this...

We study on a syllable-based acoustic modeling method for Japanese spontaneous speech recognition. Traditionally, mora-based acoustic models have been adopted for Japanese read speech recognition systems. In this paper, syllable-based unit and mora-based unit are clearly distinguished in their definition, and syllables are shown to be more suitable as an acoustic model for Japanese spontaneous ...

This paper addresses the issues in the recognition of the most frequently occurring Consonant-Vowel (CV) units of speech in Indian languages. Two major issues in the recognition of CV units are the large number of CV classes and high similarity among several CV units. In this paper, we propose two level acoustic models comprising of Hidden Markov Models (HMM) and Support Vector Machines (SVM) t...