Cross-language retrieval of spontaneous speech combines the challenges of working with noisy automated transcription and language translation. The CLEF 2005 CrossLanguage Speech Retrieval (CL-SR) task provides a standard test collection to investigate these challenges. We show that we can improve retrieval performance: by careful selection of the term weighting scheme; by decomposing automated transcripts into phonetic substrings to help ameliorate transcription errors; and by combining automatic transcriptions with manually-assigned metadata. We further show that topic translation with online machine translation resources yields effective CL-SR.
A further investigation carried by REF on the CL-SR standard collection showed that retrieval effectiveness could be improved by careful selection of the term weighting scheme between the ASR and the manual metadata.
Investigating Cross-Language Speech Retrieval For A Spontaneous Conversational Speech Collection
Human Language Technology Conference And Meeting Of The North American Association For Computational Linguistics - Short Papers
Computer Science