Automated Scoring of Nonnative Speech Using the SpeechRaterSM v. 5.0 Engine

L Chen, K Zechner, SY Yoon, K Evanini… - ETS Research …, 2018 - Wiley Online Library
This research report provides an overview of the R&D efforts at Educational Testing Service
related to its capability for automated scoring of nonnative spontaneous speech with the …

Determinants affecting teachers' adoption of AI-based applications in EFL context: An analysis of analytic hierarchy process

Y Du, H Gao - Education and Information Technologies, 2022 - Springer
Artificial Intelligence (AI) has been exerting a revolutionary and profound impact on the
teaching of English as Foreign Language (EFL) for decades. In spite of these acknowledged …

Exploring deep learning architectures for automatically grading non-native spontaneous speech

J Tao, S Ghaffarzadegan, L Chen… - 2016 IEEE International …, 2016 - ieeexplore.ieee.org
We investigate two deep learning architectures reported to have superior performance in
ASR over the conventional GMM system, with respect to automatic speech scoring. We use …

Automatic assessment of English proficiency for Japanese learners without reference sentences based on deep neural network acoustic models

J Fu, Y Chiba, T Nose, A Ito - Speech Communication, 2020 - Elsevier
Speech-based computer-assisted language learning (CALL) systems should recognize the
utterances of the learner with high accuracy and evaluate the language proficiency of the …

Etlt 2021: Shared task on automatic speech recognition for non-native children's speech

R Gretter, M Matassoni, D Falavigna, A Misra… - 2021 - repository.cam.ac.uk
The paper presents the Second ASR Challenge for Non-native Children's Speech proposed
as a Special Session at Interspeech 2021, following the successful first challenge at …

Overview of the interspeech tlt2020 shared task onasr for non-native children's speech

R Gretter, M Matassoni, D Falavigna, K Evanini… - … of Interspeech 2020, 2020 - cris.fbk.eu
We present an overview of the ASR challenge for non-native children's speech organized for
a special session at Interspeech2020. The data for the challenge was obtained in the …

[HTML][HTML] Gauging the validity of machine learning-based temporal feature annotation to measure fluency in speech automatically

R Matsuura, S Suzuki, K Takizawa, M Saeki… - Research Methods in …, 2025 - Elsevier
Abstract Machine learning (ML) techniques allow for automatically annotating various
temporal speech features, particularly by the cascade connection of ML-based modules …

Automated speech scoring system under the lens: evaluating and interpreting the linguistic cues for language proficiency

P Bamdev, MS Grover, YK Singla, P Vafaee… - International Journal of …, 2023 - Springer
Abstract English proficiency assessments have become a necessary metric for filtering and
selecting prospective candidates for both academia and industry. With the rise in demand for …