i-Vector Modeling of Speech Attributes for Automatic Foreign Accent Recognition

—We propose a unified approach to automatic foreign accent recognition. It takes advantage of recent technology advances in both linguistics and acoustics based modeling techniques in automatic speech recognition (ASR) while overcoming the issue of a lack of a large set of transcribed data often required in designing state-of-the-art ASR systems. The key idea lies in defining a common set of fundamental units “universally” across all spoken accents such that any given spoken utterance can be transcribed with this set of “accentuniversal” units. In this study, we adopt a set of units describing manner and place of articulation as speech attributes. These units exist in most spoken languages and they can be reliably modeled and extracted to represent foreign accent cues. We also propose an i-vector representation strategy to model the feature streams formed by concatenating these units. Testing on both the Finnish national foreign language certificate (FSD) corpus and the En...

• Type: Journal
• Year: 2016
• Where: TASLP
• Authors: Hamid Behravan, Ville Hautamäki, Sabato Marco Siniscalchi, Tomi Kinnunen, Chin-Hui Lee
• Keywords: Software Engineering, TASLP 2016