2 Individual Pronunciation Coaching The difficulties experienced while learning the pronunciation of a second language do not only depend on the mother tongue of the learners but also on individual differences between learners. Even students of the same mother tongue and with a very similar learning background show huge differences in their individual pronunciation. Learners also differ in term...

We describe a new language-independent technique for automatically identifying errors in an electronic pronunciation dictionary by analyzing the source of conflicting patterns directly. We evaluate the effectiveness of the technique in two ways: we perform a controlled experiment using artificially corrupted data (allowing us to measure precision and recall exactly); and then apply the techniqu...

Modeling pronunciation variation is key for recognizing conversational speech. Rather than being limited to dictionary modeling, we argue that triphone clustering is an integral part of pronunciation modeling. We propose a new approach called enhanced tree clustering. This approach, in contrast to traditional decision tree based state tying, allows parameter sharing across phonemes. We show tha...

The ultimate aim of the research reported on here is to develop an automatic testing system for Dutch pronunciation. In the experiment described in this paper automatic scores of telephone speech produced by native and non-native speakers of Dutch are compared with speci®c, i.e., temporal and segmental, and global pronunciation ratings assigned by three groups of experts: three phoneticians and...

This paper examines the phenomenon of spelling pronunciation in Ghanaian English and shows that it has become one of the features of pronunciation that have diverged from „RP‟ (Received Pronunciation), the standard norm of English language proficiency that is taught to Ghanaians. The empirical investigation of spelling pronunciation was a selection of 50 words of English based on observation of...

This paper presents different methods of handling pronunciation variations in Cantonese large-vocabulary continuous speech recognition. In an LVCSR system, three knowledge sources are involved: a pronunciation lexicon, acoustic models and language models. In addition, a decoding algorithm is used to search for the most likely word sequence. Pronunciation variation can be handled by explicitly m...

PLASER is a multimedia tool with instant feedback designed to teach English pronunciation for high-school students of Hong Kong whose mother tongue is Cantonese Chinese. The objective is to teach correct pronunciation and not to assess a student’s overall pronunciation quality. Major challenges related to speech recognition technology include: allowance for non-native accent, reliable and corre...

Generally, a speech recognition system uses a fixed set of pronunciations according to the dictionary for training and decoding. However, even a well-defined dictionary cannot be used to support all variations in human’s pronunciation. Besides, in order to cover all possible pronunciations, the size of the dictionary would be too large to implement. This paper presents efficient strategies for ...