The present paper examines general concepts behind automatic speech- and language processing technologies set against the requirements of audio archives. It is argued that current technologies in automatic speech recognition, text-analysis and speaker-technologies may be a good starting point to index speech from digitized archive audio material to create low-level descriptors for basic text mining. Together with semantic annotations created the traditional way, the additional information may be the key to an extended archival mining approach.
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