TEACHER STUDENT TRAINING FREE SPEAKING LANGUAGE ASSESSMENT
A high performance automatic speech recognition (ASR) system is an
important constituent component of an automatic language assessment
system for free speaking language tests. The ASR system is required to
be capable of recognising non-native spontaneous English speech and to
be deployable under real-time conditions. The performance of ASR systems
can often be significantly improved by leveraging upon multiple systems
that are complementary, such as an ensemble. Ensemble methods, however,
can be computationally expensive, often requiring multiple decoding
runs, which makes them impractical for deployment. In this paper, a
lattice-free implementation of sequence-level teacher-student training
is used to reduce this computational cost, thereby allowing for
real-time applications. This method allows a single student model to
emulate the performance of an ensemble of teachers, but without the need
for multiple decoding runs. Adaptations of the student model to
speakers from different first languages and grades are also
explored.teacher student training free speaking language assessment
There is a high demand around the world for the learning of English as a
second language. Assessment of a learner’s language proficiency is a
key part of learning both in measuring progress made and for formal
qualifications required e.g. for entrance to university or to obtain a
job. Given the high demand from English learners, it will be very
difficult to train sufficient examiners and the introduction of
automatic markers will be beneficial especially for practice situations.
https://speakinenglish.in/
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