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Towards automatic assessment of spontaneous spoken English

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Gales, MJF 
Knill, KM 
Kyriakopoulos, K 
Malinin, A 

Abstract

With increasing global demand for learning English as a second language, there has been considerable interest in methods of automatic assessment of spoken language proficiency for use in interactive electronic learning tools as well as for grading candidates for formal qualifications. This paper presents an automatic system to address the assessment of spontaneous spoken language. Prompts or questions requiring spontaneous speech responses elicit more natural speech which better reflects a learner’s proficiency level than read speech. In addition to the challenges of highly variable non-native, learner, speech and noisy real-world recording conditions, this requires any automatic system to handle disfluent, non-grammatical, spontaneous speech with the underlying text unknown. To handle these, a strong deep learning based speech recognition system is applied in combination with a Gaussian Process (GP) grader. A range of features derived from the audio using the recognition hypothesis are investigated for their efficacy in the automatic grader. The proposed system is shown to predict grades at a similar level to the original examiner graders on real candidate entries. Interpolation with the examiner grades further boosts performance. The ability to reject poorly estimated grades is also important and measures are proposed to evaluate the performance of rejection schemes. The GP variance is used to decide which automatic grades should be rejected. Back-off to an expert grader for the least confident grades gives gains.

Description

Keywords

Automatic assessment of spoken english, Spontaneous speech, Pronunciation, Gaussian process, Rejection scheme

Journal Title

Speech Communication

Conference Name

Journal ISSN

0167-6393
1872-7182

Volume Title

104

Publisher

Elsevier BV
Sponsorship
Cambridge Assessment (unknown)
Cambridge Assessment English