The purposes of this research were to classify the types error made by students in pronouncing silent letter, count total errors that made, and know source errors. subjects at second semester English Education Raden Intan State Islamic University Lampung. H class afforementioned sample purposing sampling technique was used 29 students. result showed there 4 errors; omission, addition, misformat...

French is known to be a language with major pronunciation irregularities at word endings with consonants. Particularly, the well-known phonetic phenomenon called Liaison is one of the major issues for French phonetizers. Rule-based methods have been used to solve these issues. Yet, the current models still produce a great number of pronunciation errors to be used in 2nd language learning applic...

We investigate the detection of spoken terms in conversational speech using phoneme recognition with the objective of achieving smaller index size as well as faster search speed. Speech is processed and indexed as a sequence of one best phoneme sequence. We propose the use of a probabilistic pronunciation model for the search term to compensate for the errors in the recognition of phonemes. Thi...

Visually and phonologically similar characters are major contributing factors for errors in Chinese text. By defining appropriate similarity measures that consider extended Cangjie codes, we can identify visually similar characters within a fraction of a second. Relying on the pronunciation information noted for individual characters in Chinese lexicons, we can compute a list of characters that...

For the purpose of developing pronunciation training tools for second language learning a corpus of non-native speech data has been collected, which consists of almost 18 hours of annotated speech signals spoken by Italian and German learners of English. The corpus is based on 250 utterances selected from typical second language learning exercises. It has been annotated at the word and the phon...

This paper presents a new technique in the development of tools for Computer-Aided Language Learning (CALL) in Second Language (L2) pronunciation training. Instead of the usual pinpointing and feedback strategies, which address all production errors in the L2 speaker equally, this technique aims at honing in on where a pronunciation error can lead to a confusion in the transmission of the messa...

To improve the recognition accuracy for spontaneous conversational speech, we collected a corpus to study how spontaneous conversational speech differs from read style speech. The corpus consists of two parts: 1) spontaneous conversational speech and 2) read speech with the same word transcriptions as the conversational speech. In word and phone recognition experiments, it was confirmed that, f...

The usefulness of teaching pronunciation in language instruction remains controversial. Though past research suggests that teachers can make little or no difference in improving their students’ pronunciation,  current  findings  suggest  that  second  language  pronunciation  can  improve  to  be near  native-like  with  the  implementation  of  certain  criteria  such  as  the  utilization  of...

Information on what kinds of mispronunciation cause the greatest loss in naturalness can be used in guidance to help learners achieve their goals of speaking with good pronunciation. We recorded Japanese words spoken by bilinguals in Tokyo Japanese and in foreign accents (English and Korean) and morphed them together with STRAIGHT emphasizing different acoustic parameters. By using STRAIGHT, we...

In this paper we investigate unsupervised name transliteration using comparable corpora, corpora where texts in the two languages deal in some of the same topics — and therefore share references to named entities — but are not translations of each other. We present two distinct methods for transliteration, one approach using an unsupervised phonetic transliteration method, and the other using t...