Investigating Bilingual Deep Neural Networks for Automatic Recognition of Code-switching Frisian Speech

Abstract

In this paper, a code-switching automatic speech recognition (ASR) system built for the Frisian language is described. Frisian is mostly spoken in the province Fryslân which is located in the north of the Netherlands. The native speakers of Frisian are mostly bilingual and often code-switch in daily conversations due to the extensive influence of the Dutch language. In the scope of the FAME! Project, the influence of this unforeseen language switching on modern ASR systems will be investigated with the objective of building a robust recognizer that can handle this phenomenon. For this purpose, in this work, we design a bilingual deep neural network (DNN)-based ASR system and investigate the impact of bilingual DNN training in the context of code-switching speech.