Abstract
This paper presents the architecture of a system for full-text search by speech data based on a global search index that combines information about all speech recordings in the archive. The architecture includes two independent blocks: an indexing block, and a block for building and performing a search query. In order to process speech recordings, it uses an automatic speech recognition system (ASR) with a linguistic decoder based on weighted finite-state transducers framework (WFST), which generates word lattices. Lattices are sequentially converted to confusion networks and inverse indexes. It allows taking into account all the word hypotheses generated during decoding. The proposed solution expands the applicability of speech analytics systems for those cases when the word error rate is high, such as the processing of speech recordings collected under difficult acoustic conditions or in low-resource languages.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Scientific and Technical Journal of Information Technologies, Mechanics and Optics
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.