We propose the use of speech attributes, such as voicing and aspiration, to address two key
research issues in computer assisted pronunciation training (CAPT) for L2 learners, namely …

In this paper, we utilize manner and place of articulation features and deep neural network
models (DNNs) with long short-term memory (LSTM) to improve the detection performance …

We investigate the effectiveness of soft-target tone labels and sequential context information
for mispronunciation detection of Mandarin lexical tones pronounced by second language …

In this paper, we investigate the effectiveness of articulatory information for Mandarin tone
modeling and recognition in a deep neural network–hidden Markov model (DNN-HMM) …

We propose a novel decision tree based framework to detect phonetic mispronunciations
produced by L2 learners caused by using inaccurate speech attributes, such as manner and …

Aiming at detecting pronunciation errors produced by second language learners and
providing corrective feedbacks related with articulation, we address effective articulatory …

Acoustic features extracted in the vicinity of landmarks have demonstrated their usefulness
for detecting mispronunciation in our recent work [1, 2]. Traditional approaches of detecting …

Automatic tone recognition is useful for Mandarin spoken language processing. However,
the complex F0 variations from the tone co-articulations and the interplay effects among …

We propose three techniques to improve mispronunciation detection of Mandarin tones of
second language (L2) learners using tone-based extended recognition network (ERN). First …

Automatic evaluation of tonal production plays an important role in a tonal language
Computer-Assisted Pronunciation Training (CAPT) system. In this paper, we propose an …