Post-processing of the recognized speech for web presentation of large audio archive

摘要

This paper deals with a post-processing phase of automatic transcription of spoken documents stored in the large Czech Radio audio archive (containing hundreds of thousands of recordings). The ultimate goal of the project is to transcribe them and to allow public access to their content. In this paper we focus on methods and algorithms for unsupervised post-processing of automatically recognized recordings. The post-processing is adapted for the needs of the web presentation of the archive. Up to now it has been used to process about 60,000 audio documents. We present the overall structure of the system as well as its core modules - speech recognition engine, speaker diarization module and final text processing. Special attention is paid to the punctuation issue. The punctuation accuracy is evaluated and compared to human use. In the final part of the paper we propose further improvements and ideas for the future research.