Inference Network-based Indonesian Spoken Query Information Retrieval

Query term misrecognition caused by the speech recognizer is one of the important issues in the spoken query information retrieval. The misrecognized term in the transcribed query leads to the retrieval of irrelevant documents. To raise the correct ranking of the retrieved documents, we use a speech recognition confidence score based on word posterior probability to weight the term in the inference network-based (IN-based) Indonesian information retrieval system. Our result shows that this technique can improve the mean reciprocal rank (MRR) score of the retrieved documents.