Journal Article

Performance of Forced-Alignment Algorithms on Children's Speech

Berisha, Visar, Hustad, Katherine C., Liss, Julie, Kawabata, Kan, Mahr, Tristan J.

2021

Overview

Purpose: Acoustic measurement of speech sounds requires first segmenting the speech signal into relevant units (words, phones, etc.). Manual segmentation is cumbersome and time consuming. Forced-alignment algorithms automate this process by aligning a transcript and a speech sample. We compared the phoneme-level alignment performance of five available forced-alignment algorithms on a corpus of child speech. Our goal was to document aligner performance for child speech researchers. Method: The child speech sample included 42 children between 3 and 6 years of age. The corpus was force-aligned using the Montreal Forced Aligner with and without speaker adaptive training, triphone alignment from the Kaldi speech recognition engine, the Prosodylab-Aligner, and the Penn Phonetics Lab Forced Aligner. The sample was also manually aligned to create gold-standard alignments. We evaluated alignment algorithms in terms of accuracy (whether the interval covers the midpoint of the manual alignment) and difference in phone-onset times between the automatic and manual intervals. Results: The Montreal Forced Aligner with speaker adaptive training showed the highest accuracy and smallest timing differences. Vowels were consistently the most accurately aligned class of sounds across all the aligners, and alignment accuracy increased with age for fricative sounds across the aligners too. Conclusion: The best-performing aligner fell just short of human-level reliability for forced alignment. Researchers can use forced alignment with child speech for certain classes of sounds (vowels, fricatives for older children), especially as part of a semi-automated workflow where alignments are later inspected for gross errors.

• Publisher: American Speech-Language-Hearing Association
• Subject: Accuracy / Acoustic phonetics / Acoustics / Adolescent / Age Differences / Algorithms / Alignment / Annotations / Auditory Evaluation / Automation / Brain research / Child / Child language / Children / Children & youth / Comparative Analysis / Computational Linguistics / Corpus linguistics / Dictionaries / English / Errors / Fricatives / Humans / Interrater Reliability / Language Tests / Mathematics / Measurement / Medical screening / Middle class / North American English / Older children / Phonemes / Phonemics / Phonetics / Reliability / Reproducibility of Results / Researchers / Segmentation / Special Issue: Selected Papers From the 2020 Conference on Motor Speech—Basic Science and Clinical Innovation / Speech / Speech Language Pathology / Speech perception in children / Speech Production Measurement / Speech recognition / Speech sounds / Speech Tests / Speeches / Stimuli / Suprasegmentals / Telephones / Training / Transcripts (Written Records) / Voice recognition / Vowels / Young Children