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A Survey on Spoken Language Understanding: Recent Advances and New Frontiers (2103.03095v2)

Published 4 Mar 2021 in cs.CL

Abstract: Spoken Language Understanding (SLU) aims to extract the semantics frame of user queries, which is a core component in a task-oriented dialog system. With the burst of deep neural networks and the evolution of pre-trained LLMs, the research of SLU has obtained significant breakthroughs. However, there remains a lack of a comprehensive survey summarizing existing approaches and recent trends, which motivated the work presented in this article. In this paper, we survey recent advances and new frontiers in SLU. Specifically, we give a thorough review of this research field, covering different aspects including (1) new taxonomy: we provide a new perspective for SLU filed, including single model vs. joint model, implicit joint modeling vs. explicit joint modeling in joint model, non pre-trained paradigm vs. pre-trained paradigm;(2) new frontiers: some emerging areas in complex SLU as well as the corresponding challenges; (3) abundant open-source resources: to help the community, we have collected, organized the related papers, baseline projects and leaderboard on a public website where SLU researchers could directly access to the recent progress. We hope that this survey can shed a light on future research in SLU field.

Citations (81)

Summary

  • The paper provides a comprehensive survey of recent innovations in spoken language understanding, detailing cutting‐edge neural and end-to-end approaches.
  • It systematically categorizes methodologies based on benchmark datasets and performance metrics to highlight significant improvements over legacy systems.
  • The paper outlines promising future directions, emphasizing multimodal integration and automated techniques to enhance speech processing.

Overview of Author Formatting in IJCAI-21 Proceedings

The paper "IJCAI--21 Example on typesetting multiple authors" serves as a practical guide for formatting author information specifically for the IJCAI-21 Proceedings using LaTeX. The primary focus is on demonstrating the syntax and organization necessary to accurately represent multiple authors, affiliations, and emails in academic submissions.

Structure and Content

The document is organized into several sections, each addressing a specific aspect of author information formatting. Key sections include:

  1. Introduction: A concise statement summarizing the paper's purpose—providing an example of author formatting.
  2. Author Names: Describes the necessary LaTeX commands to ensure proper separation of author names. The paper advises using \and for non-terminal authors and \And for the penultimate author to maintain clarity in listing.
  3. Affiliations: Guidance on starting the affiliations section using the \affiliations command. Each affiliation requires termination with a newline to ensure correct indentation and alignment.
  4. Mapping Authors to Affiliations: Addresses complex scenarios where authors have individual or shared affiliations. It emphasizes using numeric superscripts rather than symbols to denote affiliations, which preserves symbols for footnotes.
  5. Emails: Although optional, this section details how to include author emails effectively. It explains the syntax for grouping emails with the same domain to reduce redundancy and maintain readability.

Technical Insights

The paper effectively elucidates the nuances of typesetting author information, significantly simplifying a typically error-prone task for researchers unfamiliar with the intricacies of IJCAI's formatting requirements. By strictly using numeric superscripts and clearly differentiating between newline commands, the paper ensures clarity and precision in author affiliation mapping. Furthermore, the approach to contracting emails reduces visual clutter, an often overlooked yet crucial aspect of typesetting.

Implications and Future Directions

This guide, while relatively straightforward, has practical significance. Proper formatting is critical for maintaining consistency and professionalism in conference proceedings, impacting both the perception and accessibility of research papers. While the paper focuses on IJCAI-21, its principles can extend to other academic conferences with similar requirements, aiding in broader standardization efforts.

Speculatively, as LaTeX continues to be the preferred tool for academic typesetting, enhancements in template standardization could further streamline such processes. Automation tools or editor plugins that integrate these guidelines could significantly reduce author burden, enhancing productivity and accuracy in future submissions. These advancements might also facilitate the inclusivity of authors unfamiliar with LaTeX, broadening participation in academic discourse.

In conclusion, while the document serves as a utilitarian guide to a specific aspect of conference preparation, it plays a crucial role in maintaining scholarly standards and enhancing the presentation of collaborative research efforts.

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