no code implementations • ROCLING 2022 • Tzu-I Wu, Tien-Hong Lo, Fu-An Chao, Yao-Ting Sung, Berlin Chen
Due to the surge in global demand for English as a second language (ESL), developments of automated methods for grading speaking proficiency have gained considerable attention.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • ROCLING 2022 • Jung-En Haung, Hou-Chiang Tseng, Li-Yun Chang, Hsueh-Chih Chen, Yao-Ting Sung
Feature analysis of Chinese characters plays a prominent role in “character-based” education.
no code implementations • 11 Apr 2024 • Tien-Hong Lo, Fu-An Chao, Tzu-I Wu, Yao-Ting Sung, Berlin Chen
Automated speaking assessment (ASA) typically involves automatic speech recognition (ASR) and hand-crafted feature extraction from the ASR transcript of a learner's speech.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 29 May 2023 • Fu-An Chao, Tien-Hong Lo, Tzu-I Wu, Yao-Ting Sung, Berlin Chen
Automatic Pronunciation Assessment (APA) plays a vital role in Computer-assisted Pronunciation Training (CAPT) when evaluating a second language (L2) learner's speaking proficiency.
no code implementations • 17 Oct 2021 • Tien-Hong Lo, Yao-Ting Sung, Berlin Chen
Recently, end-to-end (E2E) models, which allow to take spectral vector sequences of L2 (second-language) learners' utterances as input and produce the corresponding phone-level sequences as output, have attracted much research attention in developing mispronunciation detection (MD) systems.
no code implementations • IJCLCLP 2021 • Fu-An Chao, Tien-Hong Lo, Shi-Yan Weng, Shih-Hsuan Chiu, Yao-Ting Sung, Berlin Chen
This paper describes the NTNU ASR system participating in the Formosa Speech Recognition Challenge 2020 (FSR-2020) supported by the Formosa Speech in the Wild project (FSW).