In this paper, we address the importance of pronunciation and acoustic model adaptation in multilingual speech recognition. When aiming at modeling several languages simultaneously, the degree of speaker and language variability is even greater than when concentrating on only one language. To compensate the pronunciation variability across various speaker, bi-lingual pronunciation modeling is p...

This paper investigates the features that determine the sentence pronunciation difficulty for Korean speakers of English. We selected three types of features: length, word frequency, and phonemes that Korean speakers generally replace with other phonemes. We used support vector machines and a multiple linear regression model to determine the pronunciation difficulty of given sentences, and meas...

In this study we present various techniques to evaluate the pronunciation of students of a foreign language without any knowledge of the uttered text. Previous attempts have shown that it is feasible to evaluate the pronunciation of a non-native speaker by having implicit or explicit knowledge of the uttered text, provided that enough utterances are available. Our approach is to use characteris...

A model of pronunciation of words in discourse context has been induced from the annotation of a spoken language corpus. The information included in the annotation is a set of variables hypothesised to be important for the pronunciation of words in discourse context. The annotation is connected to segmentally defined units on tiers corresponding to linguistically relevant units: the discourse, ...

Objective pronunciation assessment plays a very important role in the Mandarin Proficiency Test. But it still has a long way to go before it reaches the level of success. In this paper, the novel Mandarin objective pronunciation assessment pronunciation of is proposed. The standard of Mandarin pronunciation is divided into six levels. The mandarin pronunciation is divided into consonant, vowel ...

Introducing pronunciation models into decoding has been proven to be benefit to LVCSR. In this paper, a discriminative pronunciation modeling method is presented, within the framework of the Minimum Phone Error (MPE) training for HMM/GMM. In order to bring the pronunciation models into the MPE training, the auxiliary function is rewritten at word level and decomposes into two parts. One is for ...

This paper presents an approach to automatically extract and evaluate the “stability” of pronunciation variants (i.e., adequacy of the model to accommodate this variability), based on multiple pronunciations of each lexicon words and the knowledge of a reference baseform pronunciation. Most approaches toward modelling pronunciation variability in speech recognition are based on the inference (t...