#5888. Symbolic and Statistical Learning Approaches to Speech Summarization: A Scoping Review

August 2026publication date
Proposal available till 03-06-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Theoretical Computer Science;
Human-Computer Interaction;
Software;
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More details about the manuscript: Science Citation Index Expanded or/and Social Sciences Citation Index
Abstract:
Speech summarization techniques take human speech as input and then output an abridged version as text or speech. Speech summarization has applications in many domains from information technology to health care, for example improving speech archives or reducing clinical documentation burden. This scoping review maps close to 2 decades of speech summarization literature, spanning from the early machine learning works up to ensemble models, with no restrictions on the language summarized, research method, or paper type.
Keywords:
Abstractive summarization; Automatic speech recognition; Extractive summarization; Speech summarization; Spontaneous speech

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