In this research, we proposed a system that can use automatically generated templates for detecting Chinese spelling error. At first, we use frequently used Chinese characters to produce the Chinese confusion set. Based on a dictionary, our system automatically generated negative vocabulary template with the help of Chinese confusion set. Error types include pronunciation-related errors and rad...

This study investigates whether a computer assisted pronunciation training (CAPT) system can help young learners improve word-level pronunciation skills in English as a foreign language at a level comparable to that achieved through traditional teacher-led training. The pronunciation improvement of a group of learners of 11 years of age receiving teacher-fronted instruction was compared to that...

We present a Wizard-of-Oz experiment examining phonetic accommodation of human interlocutors in the context human-computer interaction. Forty-two native speakers German engaged dynamic spoken interaction with simulated virtual tutor for learning language called Mirabella. Mirabella was controlled by experimenter and used either natural or hidden Markov model-based synthetic speech to communicat...

In children with cleft lip and palate speech disorders appear often. One major disorder amongst them is hypernasality. This is the first study which shows that it is possible to automatically detect hypernasality in connected speech without any invasive means. Therefore, we investigated MFCCs and pronunciation features. The pronunciation features are computed from phoneme confusion probabilitie...

Spontaneous speech produced in sober and intoxicated conditions has been compared in information theoretic terms on the phoneme and word level to examine phonological and lexical aspects of intoxication. Word level entropy has been calculated to capture roughly the effect of alcohol on cognitive lexical creativity. Phoneme level entropy is intended to reflect heavy tongue influences on phoneme ...

Feedback on pronunciation is vital for spoken language teaching. Automatic pronunciation evaluation and feedback can help non-native speakers to identify their errors, learn sounds and vocabulary, and improve their pronunciation performance. Such speech recognition can be performed using Sphinx trained on a database of native exemplar pronunciation and non-native examples of frequent mistakes. ...

Introducing pronunciation models into decoding has proven beneficial for LVCSR. As Minimum Phone Error (MPE) training has almost become a standard scheme for acoustic modeling, a discriminative pronunciation modeling method is investigated under the framework of MPE training. In order to bring the pronunciation models into MPE training, the auxiliary function of MPE training is rewritten at wor...

In this paper, we present our latest investigations on pronunciation modeling and its impact on ASR. We propose completely automatic methods to detect, remove, and substitute inconsistent or flawed entries in pronunciation dictionaries. The experiments were conducted on different tasks, namely (1) word-pronunciation pairs from the Czech, English, French, German, Polish, and Spanish Wiktionary [...

This paper describes how the performance of a continuous speech recognizer for Dutch has been improved by modeling pronunciation variation. We used three methods to model pronunciation variation. First, within-word variation was dealt with. Phonological rules were applied to the words in the lexicon, thus automatically generating pronunciation variants. Secondly, cross-word pronunciation variat...

In this paper, we focus on the modeling of coarticulation and pronunciation variation in Automatic Speech Recognition systems (ASR). Most ASR systems explicitly describe these production phenomena through context-dependent phoneme models and multiple pronunciation lexicons. Here, we explore the potential benefit of using feature spaces covering longer time segments in terms of implicit modeling...