The paper describes the use of phonetic transcription rules in a component for diagnosis of pronunciation errors produced by students of a foreign language. The module is part of a computer-aided language learning tool designed to report pronunciation problems by Italian and German non-native speakers of English (Herron et al., 1999). It generates a number of possible pronunciation candidates t...

This research presents an investigation performed on the ASU corpus. We analyse to what extent does the pronunciation of intended words reflects in spelling errors done by L2 Swedish learners. We also propose a method that helps to automatically discriminate the misspellings affected by pronunciation from other types of misspellings.

For the purpose of pronunciation assessment and training in a second language both read and spontaneous speech are employed. In this paper we present the results of a study on the nature o f phoneme errors in Dutch read and spontaneous non-native speech and discuss the possible consequences and relevance of these findings for the purpose of developing Computer Assisted Pronunciation Training sy...

This research is aimed at analyzing and improving automatic pronunciation error detection in a second language. Dutch vowels spoken by adult non-native learners of Dutch are used as a test case. A first study on Dutch pronunciation by L2 learners with different L1s revealed that vowel pronunciation errors are relatively frequent and often concern subtle acoustic differences between the realizat...

This paper investigates the connection between intelligibility and pronunciation accuracy. We compare which words in non-native English speech are likely to be misrecognized and which words are likely to be marked as pronunciation errors. We found that only 16% of the variability in word-level intelligibility can be explained by the presence of obvious mispronunciations. In some cases, a word r...

This paper describes reducing phone label errors in TTS voice building by means of modeling of speaker pronunciation variants. Each speaker has his or her own unique pronunciations (and context-dependent variations), so that no one standard lexicon is able to cover all of the speaker’s variations. Creating speaker-dependent pronunciation lexicons for automatic speech labeling of our TTS voice d...

In this paper, we present an acoustic-phonetic approach to automatic pronunciation error detection. Classifiers using techniques such as Linear Discriminant Analysis and Decision Trees were developed for three sounds that are frequently pronounced incorrectly by L2-learners of Dutch: / /, / / and / /. This paper will focus mainly on the problems with the latter phoneme. The acoustic properties ...

Automatic Speech Recognition (ASR) can be very useful in language learning tools in order to correct mistakes in the pronunciation of foreign words by non-native speakers. Most of the systems integrating ASR proposed on the market are just rejecting or accepting whole words or whole sentences. In this paper, we propose a method to identify the pronunciation errors at the phoneme level. Indeed, ...

In the area of Computer Assisted Language Learning(CALL), second language (L2) learners’ spoken data is an important resource for analysing and annotating typical L2 pronunciation errors. The annotation of L2 pronunciation errors in spoken data is not an easy task though, normally it requires manual annotation from trained linguists or phoneticians. In order to facilitate this task, in this pap...

The links between spellings and sounds in a large set of English words with consonant-vowel-consonant phonological structure were examined. orthographic rimes, or units consisting of a vowel grapheme and a final consonant grapheme, had more stable pronunciations than either individual vowels or initial consonant-plus-vowel units. In 2 large-scale studies of word pronunciation, the consistency o...