7th International Conference on Spoken Language Processing
September 16-20, 2002
In this paper we demonstrate how automatically generated transcriptions can be used to develop an effective topic classification application. Two key contributions of our work are (a) investigating the impact of unsupervised transcriptions on topic classification where the transcription system has been trained with very limited amounts of data, and (b) demonstrating the use of mixture language models that significantly improve topic classification performance.
Bibliographic reference. Iyer, Rukmini / Ma, Jeffrey / Gish, Herbert / Kimball, Owen (2002): "Training topic classifiers for conversational speech with limited data", In ICSLP-2002, 1501-1504.