Tonal errors pose a serious problem to Mandarin Chinese learners, making them stumble in their communication. The purpose of this paper is to investigate beginner level Japanese students’ difficulties in the perception and pronunciation of disyllabic words, particularly to find out which combinations of tones these errors mostly occur in. As a result, the errors made by the 10 subjects were mos...

We propose a method for modeling pronunciation variation in the context of spell checking for non-native writers of English. Spell checkers, typically developed for native speakers, fail to address many of the types of spelling errors peculiar to non-native speakers, especially those errors influenced by differences in phonology. Our model of pronunciation variation is used to extend a pronounc...

Recent research has shown that a properly designed ASRbased CALL system (Dutch-CAPT) was capable of detecting pronunciation errors and of providing comprehensible feedback on pronunciation. Since pronunciation is not the only skill required for speaking a second language, we explored the possibility of extending the Dutch-CAPT approach to other aspects of speaking proficiency like morphology an...

An inventory was compiled of pronunciation errors frequently made by foreigners speaking Dutch. On the basis of this inventory artificial errors were created in a native development corpus, which in turn were used to optimize thresholds for the Goodness of Pronunciation (GOP) algorithm. In the current study the GOP algorithm is evaluated in three different ways: (1) using a native test corpus w...

An inventory was compiled of pronunciation errors frequently made by foreigners speaking Dutch. On the basis of this inventory artificial errors were created in a native development corpus, which in turn were used to optimize thresholds for the Goodness of Pronunciation (GOP) algorithm. In the current study the GOP algorithm is evaluated in three different ways: (1) using a native test corpus w...

An inventory was compiled of pronunciation errors frequently made by foreigners speaking Dutch. On the basis of this inventory artificial errors were created in a native development corpus, which in turn were used to optimize thresholds for the Goodness of Pronunciation (GOP) algorithm. In the current study the GOP algorithm is evaluated in three different ways: (1) using a native test corpus w...

An inventory was compiled of pronunciation errors frequently made by foreigners speaking Dutch. On the basis of this inventory artificial errors were created in a native development corpus, which in turn were used to optimize thresholds for the Goodness of Pronunciation (GOP) algorithm. In the current study the GOP algorithm is evaluated in three different ways: (1) using a native test corpus w...

An inventory was compiled of pronunciation errors frequently made by foreigners speaking Dutch. On the basis of this inventory artificial errors were created in a native development corpus, which in turn were used to optimize thresholds for the Goodness of Pronunciation (GOP) algorithm. In the current study the GOP algorithm is evaluated in three different ways: (1) using a native test corpus w...