Study on Phrases Used for Semi-automatic Text-Based Speakers Names Extraction in the Czech Radio Broadcasts News

In this paper we introduce a methodology leading to the extension of speakers’ database used in the process of automatic transcription of spoken documents stored in the largest Czech Radio audio archive. We address the issue of the conversion of spoken speech to written texts – the automatic detection of speakers and their names. We work with a subset of the archive that consists of 8,020 hours of broadcasting news and 58,914,179 words within the years 1968– 2011. We observed the occurrence of thousands of speakers’ names during the period and therefore it is necessary to use their automatic or semi-automatic identification. Another investigated issue leading to the extension of speakers’ database is the co-occurrence of a speaker’s name in a specific phrase in the text transcription linked with the speaker’s change in the audio recording.