An NLP Pipeline as Assisted Transcription Tool for Speech Therapis

This work presents the design of a computer assisted transcription system for speech-language therapists and an evaluation of its core-module: the NLP pipeline. This pipeline combines a tokenizer, a lemmatizer, a part-of-speech tagger and a spellchecker in order to perform a semi-automatic annotation of speech transcriptions. The implemented module has been evaluated on a corpus of spoken interaction of children with Developmental Language Disorder (DLD) with the caregiver. Results are promising in automatic error detection but low in automatic error correction, and confirm the effectiveness within an assisted transcription tool.