# Transparent pronunciation scoring using articulatorily weighted phoneme edit distance

arXiv: https://arxiv.org/abs/1905.02639 · HTML: https://mlsanity.com/paper/1905.02639/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 May 2019.

## Built on by (most cited first, 1 of 1)

- [Compositional Phoneme Approximation for L1-Grounded L2 Pronunciation Training](https://mlsanity.com/paper/2411.10927/) (2024)

## Abstract (arXiv)

For researching effects of gamification in foreign language learning for children in the "Say It Again, Kid!" project we developed a feedback paradigm that can drive gameplay in pronunciation learning games. We describe our scoring system based on the difference between a reference phone sequence and the output of a multilingual CTC phoneme recogniser. We present a white-box scoring model of mapped weighted Levenshtein edit distance between reference and error with error weights for articulatory differences computed from a training set of scored utterances. The system can produce a human-readable list of each detected mispronunciation's contribution to the utterance score. We compare our scoring method to established black box methods.