Speech Data Augmentation for Improving Phoneme Transcriptions of Aphasic Speech Using Wav2Vec 2.0 for the PSST Challenge

Birger Moell, Jim O’Regan, Shivam Mehta, Ambika Kirkland, Harm Lameris, Joakim Gustafson, Jonas Beskow


Abstract
As part of the PSST challenge, we explore how data augmentations, data sources, and model size affect phoneme transcription accuracy on speech produced by individuals with aphasia. We evaluate model performance in terms of feature error rate (FER) and phoneme error rate (PER). We find that data augmentations techniques, such as pitch shift, improve model performance. Additionally, increasing the size of the model decreases FER and PER. Our experiments also show that adding manually-transcribed speech from non-aphasic speakers (TIMIT) improves performance when Room Impulse Response is used to augment the data. The best performing model combines aphasic and non-aphasic data and has a 21.0% PER and a 9.2% FER, a relative improvement of 9.8% compared to the baseline model on the primary outcome measurement. We show that data augmentation, larger model size, and additional non-aphasic data sources can be helpful in improving automatic phoneme recognition models for people with aphasia.
Anthology ID:
2022.rapid-1.8
Volume:
Proceedings of the RaPID Workshop - Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments - within the 13th Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Venue:
RaPID
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
62–70
Language:
URL:
https://aclanthology.org/2022.rapid-1.8
DOI:
Bibkey:
Cite (ACL):
Birger Moell, Jim O’Regan, Shivam Mehta, Ambika Kirkland, Harm Lameris, Joakim Gustafson, and Jonas Beskow. 2022. Speech Data Augmentation for Improving Phoneme Transcriptions of Aphasic Speech Using Wav2Vec 2.0 for the PSST Challenge. In Proceedings of the RaPID Workshop - Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments - within the 13th Language Resources and Evaluation Conference, pages 62–70, Marseille, France. European Language Resources Association.
Cite (Informal):
Speech Data Augmentation for Improving Phoneme Transcriptions of Aphasic Speech Using Wav2Vec 2.0 for the PSST Challenge (Moell et al., RaPID 2022)
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PDF:
https://aclanthology.org/2022.rapid-1.8.pdf