An automated essay scoring systems: a systematic literature review

D Ramesh, SK Sanampudi - Artificial Intelligence Review, 2022 - Springer
Assessment in the Education system plays a significant role in judging student performance.
The present evaluation system is through human assessment. As the number of teachers' …

On the application of large language models for language teaching and assessment technology

A Caines, L Benedetto, S Taslimipoor, C Davis… - arxiv preprint arxiv …, 2023 - arxiv.org
The recent release of very large language models such as PaLM and GPT-4 has made an
unprecedented impact in the popular media and public consciousness, giving rise to a …

Confidence estimation and deletion prediction using bidirectional recurrent neural networks

A Ragni, Q Li, MJF Gales… - 2018 IEEE Spoken …, 2018 - ieeexplore.ieee.org
The standard approach to assess reliability of automatic speech transcriptions is through the
use of confidence scores. If accurate, these scores provide a flexible mechanism to flag …

Asr-free pronunciation assessment

S Cheng, Z Liu, L Li, Z Tang, D Wang… - arxiv preprint arxiv …, 2020 - arxiv.org
Most of the pronunciation assessment methods are based on local features derived from
automatic speech recognition (ASR), eg, the Goodness of Pronunciation (GOP) score. In this …

Bi-directional lattice recurrent neural networks for confidence estimation

Q Li, PM Ness, A Ragni… - ICASSP 2019-2019 IEEE …, 2019 - ieeexplore.ieee.org
The standard approach to mitigate errors made by an automatic speech recognition system
is to use confidence scores associated with each predicted word. In the simplest case, these …

[HTML][HTML] Evaluating OpenAI's Whisper ASR: Performance analysis across diverse accents and speaker traits

C Graham, N Roll - JASA Express Letters, 2024 - pubs.aip.org
This study investigates Whisper's automatic speech recognition (ASR) system performance
across diverse native and non-native English accents. Results reveal superior recognition in …

LearnerVoice: A Dataset of Non-Native English Learners' Spontaneous Speech

H Kim, J Myung, S Kim, S Lee, D Kang… - arxiv preprint arxiv …, 2024 - arxiv.org
Prevalent ungrammatical expressions and disfluencies in spontaneous speech from second
language (L2) learners pose unique challenges to Automatic Speech Recognition (ASR) …

Automatic grammatical error detection of non-native spoken learner english

KM Knill, MJF Gales, PP Manakul… - ICASSP 2019-2019 …, 2019 - ieeexplore.ieee.org
Automatic language assessment and learning systems are required to support the global
growth in English language learning. They need to be able to provide reliable and …

Investigating the effects of task type and linguistic background on accuracy in automated speech recognition systems: Implications for use in language assessment of …

L Hannah, H Kim, EE Jang - Language Assessment Quarterly, 2022 - Taylor & Francis
As a branch of artificial intelligence, automated speech recognition (ASR) technology is
increasingly used to detect speech, process it to text, and derive the meaning of natural …

Using data augmentation and time-scale modification to improve asr of children's speech in noisy environments

HK Kathania, SR Kadiri, P Alku, M Kurimo - Applied Sciences, 2021 - mdpi.com
Current ASR systems show poor performance in recognition of children's speech in noisy
environments because recognizers are typically trained with clean adults' speech and …