Content-Based Search in Multilingual Audiovisual Documents Using the International Phonetic Alphabet

We present in this paper an approach based on the use of the International Phonetic Alphabet (IPA) for content-based indexing and retrieval of multilingual audiovisual documents. The approach works even if the languages of the document are unknown. It has been validated in the context of the "Star Challenge" search engine competition organized by the Agency for Science, Technology and Research (A*STAR) of Singapore. Our approach includes the building of an IPA-based multilingual acoustic model and a dynamic programming based method for searching document segments by "IPA string spotting". Dynamic programming allows for retrieving the query string in the document string even with a significant transcription error rate at the phone level. The methods that we developed ranked us as first and third on the monolingual (English) search task, as fifth on the multilingual search task and as first on the multimodal (audio and image) search task.