Accent Conversion with Articulatory Representations

Autor:	Siriwardena, Yashish M., Swedlow, Nathan, Howard, Audrey, Gitterman, Evan, Darcy, Dan, Espy-Wilson, Carol, Fanelli, Andrea
Rok vydání:	2024
Předmět:	Electrical Engineering and Systems Science - Audio and Speech Processing
Druh dokumentu:	Working Paper
Popis:	Conversion of non-native accented speech to native (American) English has a wide range of applications such as improving intelligibility of non-native speech. Previous work on this domain has used phonetic posteriograms as the target speech representation to train an acoustic model which is then used to extract a compact representation of input speech for accent conversion. In this work, we introduce the idea of using an effective articulatory speech representation, extracted from an acoustic-to-articulatory speech inversion system, to improve the acoustic model used in accent conversion. The idea to incorporate articulatory representations originates from their ability to well characterize accents in speech. To incorporate articulatory representations with conventional phonetic posteriograms, a multi-task learning based acoustic model is proposed. Objective and subjective evaluations show that the use of articulatory representations can improve the effectiveness of accent conversion. Comment: Accepted at INTERSPEECH 2024
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2406.05947 Zobrazit plný text záznamu View this record from Arxiv