Comparing decoding strategies for subword-based keyword spotting in low-resourced languages

Abstract

For languages with limited training resources, out-of-vocabulary (OOV) words are a significant problem, both for transcription and keyword spotting. This paper investigates the use of subword lexical units for keyword spotting. Three strate-gies for using the sub-word units are explored: 1) converting word-based lattices to subword lattices after decoding, 2) per-forming a separate decoding for each subword type, and 3) a single decoding using all possible subword units. In these ex-periments, the best performance is achieved by carrying out a separate decoding for each subword type. Further gains are at-tained through system combination. We also find that ignor-