Audio Search Based on Keyword Spotting in Arabic Language

Abstract

Keyword spotting is an important application of speech recognition. This research introduces a keyword spotting approach to perform audio searching of uttered words in Arabic speech. The matching process depends on the utterance nucleus which is insensitive to its context. For spotting the targeted utterances, the matched nuclei are expanded to cover the whole utterances. Applying this approach to Quran and standard Arabic has promising results. To improve this spotting approach, it is combined with a text search in case of the existence of a transcript. This can be applied on Quran as there is exact correspondence between the audio and text files of each verse. The developed approach starts by text search to identify the verses that include the target utterance(s). For each allocated verse, the occurrence(s) of the target utterance is determined. The targeted utterance (the reference) is manually segmented from an allocated verse. Then Keyword spotting is performed for the extracted reference to the corresponding audio file. The accuracy of the spotted utterances achieved 97%. The experiments showed that the use of the combined text and audio search has reduced the search time by 90% when compared with audio search only tested on the same content. The developed approach has been applied to non transcribed audio files (preaches and News) for searching chosen utterances. The results are promising. The accuracy of spotting was around 84% in case of preaches and 88% in case of the news.