Phonetic name matching for cross-lingual Spoken Sentence Retrieval

Abstract

Cross-lingual spoken sentence retrieval (CLSSR) remains a challenge, especially for queries including OOV words such as person names. This paper proposes a simple method of fuzzy matching between query names and phones of candidate audio segments. This approach has the advantage of avoiding some word decoding errors in automatic speech recognition (ASR). Experiments on Mandarin-English CLSSR show that phone-based searching and conventional translation-based searching are complementary. Adding phone matching achieved 26.29% improvement on F-measure over searching on state-of-the-art machine translation (MT) output and 8.83% over entity translation (ET) output.