Recognition of foreign names spoken by native speakers

Abstract

It is a challenge to develop a speech recognizer that can handle the kind of lexicons encountered in an automatic attendant or car navigation application. Such lexicons can contain several 100K entries, mainly proper names. Many of these names are of a foreign origin, and native speakers can pronounce them in different ways, ranging from a completely nativized to a completely foreignized pronunciation. In this paper we propose a method that tries to deal with the observed pronunciation variability by introducing the concept of a foreignizable phoneme, and by combining standard acoustic models with a phonologically inspired back-off acoustic model. The main advantage of the approach is that it does not require any foreign phoneme models nor foreign speech data. For the recognition of English names by means of Dutch acoustic models, we obtained a reduction of the word error rate by more than 10% relative.