Speech is like a box of

Pronunciation variability is present in both native and foreign words. Since pronunciation variability constitutes a problem for automatic speech recognition (ASR) systems, modeling pronunciation variation for ASR has been the topic of various studies. In most studies, modeling pronunciation variation was attempted within the standard framework used in mainstream ASR systems. Given that some assumptions made within this framework are not in line with the properties of speech signals and the findings in human speech recognition, and that the improvements obtained by modeling pronunciation variation within this framework have generally been small, it might be better to look for a new paradigm in which pronunciation variation can be modeled more accurately. In this paper a novel paradigm for ASR is presented, which has many potential advantages for modeling pronunciation variation.