A Survey of Automated Presentation Coaching: Systems, Methods, and Open Challenges
This survey systematically reviews automated presentation coaching systems covering pronunciation, fluency, prosody, multimodal, and Q&A tools. It introduces a five-dimensional task taxonomy (segmental pronunciation, lexical stress, suprasegmental prosody, pacing, content faithfulness) and maps surveyed systems to reveal coverage gaps. Core methods include TTS-based exemplar generation and diagnostic assessment. Open challenges include scarcity of annotated corpora, accent-fair feedback, and low-latency real-time diagnostics.
[2606.27380] A Survey of Automated Presentation Coaching: Systems, Methods, and Open Challenges
[Submitted on 11 May 2026]
Title:A Survey of Automated Presentation Coaching: Systems, Methods, and Open Challenges
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Abstract:Automated coaching for oral presentations sits at the intersection of computer-assisted pronunciation training (CAPT), prosody modeling, and speech synthesis, yet no prior work has systematically surveyed and compared existing systems along these dimensions. This survey reviews and categorizes automated presentation coaching systems, spanning pronunciation tutors, fluency and prosody coaches, multimodal trainers, and conference Q&A practice tools. We introduce a five-dimensional task taxonomy - covering segmental pronunciation, lexical stress, suprasegmental prosody, pacing, and content faithfulness - and explicitly map surveyed systems onto it to reveal coverage gaps. We further review the core technical methods these systems employ: TTS-based exemplar generation and diagnostic methods for pronunciation, prosody, and fluency assessment. Key open challenges include the scarcity of annotated presentation corpora, achieving accent-fair feedback across diverse L1 backgrounds, and delivering low-latency diagnostics for real-time rehearsal.
Comments: accepted into the BEA 2026 workshop at ACL
Subjects:
Computation and Language (cs.CL)
Cite as: arXiv:2606.27380 [cs.CL]
(or arXiv:2606.27380v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2606.27380
arXiv-issued DOI via DataCite
Submission history
From: Wen Liang [view email] [v1] Mon, 11 May 2026 23:32:45 UTC (52 KB)
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