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 how a methodological approach of combining electronic learner language data and asr technology is useful in constructing learner spoken corpora.