With the emergence of deep learning, performance automatic speech recognition (ASR) systems has remarkably improved. Especially for resource-rich languages such as English and Chinese, commercial usage been made feasible in a wide range applications. However, most are low-resource languages, presenting three main difficulties development ASR systems: (1) scarcity data; (2) uncertainty writing p...

Educators and researchers in the acquisition of L2 phonology have called for empirical assessment of the progress students make after using new methods for learning [1]. This study investigated whether unlimited access to a speech-recognition-based language learning program would improve the general goodness of pronunciation of a group of middle-aged immigrant professionals studying English in ...

Pronunciation of English language is a very important sub-skill of speaking module in second language learning process. However, it is ignored, neglected, and even never gotten least attention by the teachers, administrators, and stakeholders especially in Pakistan. Grammar, vocabulary, and the other linguistic skills such as reading and writing are emphasized whereas pronunciation has never be...

This research applies dialectometric methods to purely syntactic dialect data. It will be shown that there is geographic cohesion in syntactic variation when viewed in the aggregate. The amount of syntactic variation which can be accounted for by geography will be determined. Dialectometric techniques will be used to develop an additive measure of syntactic differences. Multidimensional scaling...

In this paper, we present a corpus annotated with dependency relationships in Japanese. It contains about 30 thousand sentences in various domains. Six domains in Balanced Corpus of Contemporary Written Japanese have part-of-speech and pronunciation annotation as well. Dictionary example sentences have pronunciation annotation and cover basic vocabulary in Japanese with English sentence equival...

We propose a method for automatically generating a pronunciation dictionary based on a pronunciation neural network that can predict plausible pronunciations (alternative pronunciations) from the canonical pronunciation. This method can generate multiple forms of alternative pronunciations using the pronunciation network. For generating a sophisticated alternative pronunciation dictionary, two ...

A lot of work has been done in deriving the pronunciation dictionary automatically from training data. These attempts focussed mainly on maximum likelihood or similar techniques. Due to the complexity and variability of the pronunciation process it is di cult to nd an adequate pronunciation model. The model will deviate from the truth. Hence, the application of maximum likelihood techniques is ...

This article reports on an action research project which investigated the value of systematically and explicitly incorporating a pronunciation sub-syllabus within the overall syllabus of a full-time post-intermediate level ESOL course. This pronunciation syllabus involved raising each individual learner’s awareness of their difficulties with pronunciation and of the main features of spoken Engl...

Pronunciation verification of children’s reading is a difficult task in itself, but automatic reading assessment software must also detect and evaluate other phenomena that influence human evaluators. Using an isolated word-reading task, we first show that humans use both pronunciation correctness (accuracy) and fluency information in their assessment of the reading ability of kindergarten to s...