arxiv_cl 90% Match Survey paper AI researchers,Speech processing engineers,NLP practitioners,Media professionals 2 weeks ago

Summarizing Speech: A Comprehensive Survey

speech-audio › speech-recognition

📄 Abstract

Abstract: Speech summarization has become an essential tool for efficiently managing and accessing the growing volume of spoken and audiovisual content. However, despite its increasing importance, speech summarization remains loosely defined. The field intersects with several research areas, including speech recognition, text summarization, and specific applications like meeting summarization. This survey not only examines existing datasets and evaluation protocols, which are crucial for assessing the quality of summarization approaches, but also synthesizes recent developments in the field, highlighting the shift from traditional systems to advanced models like fine-tuned cascaded architectures and end-to-end solutions. In doing so, we surface the ongoing challenges, such as the need for realistic evaluation benchmarks, multilingual datasets, and long-context handling.

Authors (7)

Fabian Retkowski

Maike Züfle

Andreas Sudmann

Dinah Pfau

Shinji Watanabe

Jan Niehues

+1 more

Submitted

April 10, 2025

arXiv Category

cs.CL

arXiv PDF

Key Contributions

Provides a comprehensive survey of speech summarization, examining existing datasets, evaluation protocols, and recent advancements. It highlights the shift towards cascaded and end-to-end models and identifies ongoing challenges like multilingual support and long-context handling.

Business Value

Enables better understanding and development of tools for efficiently processing and extracting information from the vast amount of spoken and audiovisual content generated daily.

Paper Metadata

Innovation Type

Survey and synthesis

Deployment Feasibility

High, as it provides a roadmap for researchers and developers.

Limitations Addressed

The loosely defined nature of speech summarization and the need for a consolidated overview of the field, including datasets, evaluation methods, and challenges.

Performance Gains

N/A (survey paper)

Technical Tags

Speech summarizationSpoken contentAudiovisual contentSpeech recognitionText summarizationMeeting summarizationDatasetsEvaluation protocolsCascaded architecturesEnd-to-end solutionsMultilingual datasetsLong-context handling

Research Topics

Information extraction from speechAutomated content summarizationSpeech processingNatural Language Processing

Methods & Architectures

Speech recognitionText summarizationFine-tuned cascaded architecturesEnd-to-end models Cascaded architecturesEnd-to-end solutions

Applications & Tasks

Media Communication Information management Accessibility Efficiently managing and accessing spoken contentSummarizing speech Speech summarizationMeeting summarizationTranscription summarization

Datasets & Benchmarks

Datasets

Existing datasets

Benchmarks

Realistic evaluation benchmarks

Quality of summarizationPerformance metrics

Related Fields

Speech ProcessingNatural Language ProcessingMachine LearningInformation RetrievalMedia Studies

Keywords

Speech SummarizationSpoken ContentAudiovisual ContentSpeech RecognitionText SummarizationMeeting SummarizationSurveyDatasetsEvaluationCascaded ModelsEnd-to-end ModelsMultilingualLong Context

Academic Context

#Information extraction from speech#Automated content summarization#Speech processing#Natural Language Processing

Commercial Potential

Potential Products

Automated meeting summarization toolsContent analysis platforms for audio/video

Target Industries

MediaBroadcastingTechnologyCorporate CommunicationsEducation

Use Case Examples

Generating summaries of recorded lecturesProviding concise overviews of business meetings

Competitive Edge

Provides a comprehensive overview and synthesis of the speech summarization field, identifying key trends and challenges.

Market Opportunity

Large and growing market for transcription and summarization services.

Revenue Models

Development of advanced summarization services.

Resource Requirements

Compute Needs

Varies depending on the specific summarization models discussed.

Data Requirements

Highlights the need for diverse and multilingual datasets.

Deployment Constraints

Challenges in handling noisy audio, accents, and long-form content.

Scalability

Discusses the need for scalable solutions for processing large volumes of speech data.

Regulatory Considerations

Production Readiness

Maturity Level

Survey of ongoing research

Time to Market

N/A (survey paper)

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