Minimizing Word Error Rate In Textual Summaries Of Spoken Language
Klaus Zechner, Alex Waibel · 2000
Automatic generation of text summaries for spoken language faces the problem of containing incorrect words and passages due to speech recognition errors. This paper describes comparative experiments where passages with higher speech recognizer confidence scores are favored in the ranking process. Results show that a relative word error rate reduction of over 10% can be achieved while at the same time the accuracy of the summary improves markedly. 1 Introduction The amount of audio data on-line has been growing rapidly in recent years, and so methods for efficiently indexing and retrieving non-textual information have become increasingly important (see, e.g., the TREC-7 branch for "Spoken Document Retrieval " (Garofolo et al., 1999)). One way of compressing audio information is the automatic creation of textual summaries which can be skimmed much faster and stored much more efficiently than the audio itself. There has been plenty of research in the area of summarizing written languag...