19. A method for identifying a block of text as relating to a topic of interest, in a system comprising a plurality of language models, including a language model for the topic of interest, the method comprising: obtaining a stream of text comprising text segments; scoring the text segments against the plurality of language models to generate language model scores for the text segments; identifying a text segment from among the text segments as block of text relating to the topic of interest if the score of the text segment against the language model for the topic of interest satisfies a predetermined condition.
19. A method for identifying a block of text as relating to a topic of interest, in a system comprising a plurality of language models, including a language model for the topic of interest, the method comprising: obtaining a stream of text comprising text segments; scoring the text segments against the plurality of language models to generate language model scores for the text segments; identifying a text segment from among the text segments as block of text relating to the topic of interest if the score of the text segment against the language model for the topic of interest satisfies a predetermined condition. 21. The method of claim 19, wherein the predetermined condition requires the score of the text segment against the language model for the topic of interest to be the lowest score among the scores of the text segment against the plurality of language models, and that the next lowest score among the scores of the text segment against the plurality of language models be greater than the score of the text segment against the language model for the topic of interest by more than a predetermined amount.