This paper reviews the research approaches used in computer-assisted pronunciation
training (CAPT), addresses the existing challenges, and discusses emerging trends and …

This paper focuses on using Convolutional Neural Network (CNN), Recurrent Neural
Network (RNN) and Connection-ist Temporal Classification (CTC) to build an end-to-end …

Mispronunciation detection and diagnosis (MDD) is a core component of computer-assisted
pronunciation training (CAPT). Most of the existing MDD approaches focus on dealing with …

In this work, we analyze phonetic and prosodic pronunciation patterns from iCALL, a speech
corpus designed to evaluate Mandarin mispronunciations by non-native speakers of …

This work deals with non-native children's speech and investigates both multi-task and
transfer learning approaches to adapt a multi-language Deep Neural Network (DNN) to …

Current leading mispronunciation detection and diagnosis (MDD) systems achieve
promising performance via end-to-end phoneme recognition. One challenge of such end-to …

This paper describes" TLT-school" a corpus of speech utterances collected in schools of
northern Italy for assessing the performance of students learning both English and German …

With the acceleration of globalization, more and more people are willing or required to learn
second languages (L2). One of the major remaining challenges facing current …

The increased need for foreign language learning, along with advances in speech
technology have heightened interest in computer-assisted pronunciation teaching (CAPT) …

We present OOD-Speech, the first out-of-distribution (OOD) benchmarking dataset for
Bengali automatic speech recognition (ASR). Being one of the most spoken languages …