Constructing a longitudinal learner corpus to track L2 spoken English

The main purposes of this article are to provide an overview of a research project on a longitudinal learner spoken corpus and to share procedures related to the transcription of learners' utterances from audio files using automated speech recognition (ASR) technology (IBM Watson Speech-to-text).The data of the corpus were collected twice or thrice a year for three consecutive years from 2016, creating eight data collection points altogether. They were gathered from 120 secondary school students who had been learning English in an English as a Foreign Language context for three years. The students were asked to take a monologue speaking test, the Telephone Standard Speaking Test, consisting of various tasks. The overall discussion of the article focuses on the details of this project and highlights howa methodological approach of combining electronic learner language data and ASR technology is useful in constructing learner spoken corpora.