Searching the Audio Notebook: Keyword Search in Recorded Conversation

MIT’s Audio Notebook added great value to the note-taking process by retaining audio recordings, e.g. during lectures or interviews. The key was to provide users ways to quickly and easily access portions of interest in a recording. Several non-speech-recognition based techniques were employed. In this paper we present a system to search directly the audio recordings by key phrases. We have identified the user requirements as accurate ranking of phrase matches, domain independence, and reasonable response time. We address these requirements by a hybrid word/phoneme search in lattices, and a supporting indexing scheme. We will introduce the ranking criterion, a unified hybrid posterior-lattice representation, and the indexing algorithm for hybrid lattices. We present results for five different recording sets, including meetings, telephone conversations, and interviews. Our results show an average search accuracy of 84%, which is dramatically better than a direct search in speech recognition transcripts (less than 40% search accuracy).