Automated forced alignment tools — widely used to time-align transcripts with audio — were built primarily on adult speech. WISC Lab research has documented how alignment errors affect automated pronunciation scoring in children, and a new tunable system based on deep learning addresses some of these limitations. If you’re building or using pipelines that include child speech data, this post covers what the error rates look like in practice and what the new system offers.