2022 IEEE Spoken Language Technology Workshop (SLT 2022)

Top Research Topics at Spoken Language Technology Workshop?

• Speech recognition (63.16%)
• Artificial intelligence (61.84%)
• Natural language processing (39.98%)

The primary areas of discussion in the conference are Speech recognition, Artificial intelligence, Natural language processing, Artificial neural network and Hidden Markov model. The event focuses on Speech recognition but the discussions also offer insight into other areas such as Data modeling, Feature extraction and Word (computer architecture). The studies tackled, which mainly focus on Feature extraction, apply to Feature (machine learning) as well.

The in-depth study on Word (computer architecture) also explores topics in the intersecting field of Vocabulary. The work on Artificial intelligence tackled in it brings together disciplines like Context (language use), Machine learning and Pattern recognition. Speaker recognition is the primary subject of Pattern recognition works presented in the conference.

The research on Natural language processing featured in it combines topics in other fields like Speech corpus, Utterance, Dialog box and Task analysis. The Hidden Markov model study featured in the event draws connections with the study of Speech synthesis. Some problems in Language model that were presented in it overlapped with concepts under Recurrent neural network and Decoding methods.

What are the most cited papers published at the conference?

• Context dependent recurrent neural network language model (483 citations)
• Speaker Recognition from Raw Waveform with SincNet (259 citations)
• Spoken language understanding using long short-term memory neural networks (254 citations)

Research areas of the most cited articles at Spoken Language Technology Workshop:

The published articles focus largely on the fields of Artificial intelligence, Speech recognition, Natural language processing, Artificial neural network and Feature extraction. The featured Artificial intelligence studies in the published papers mainly concentrate on Pattern recognition but also cover areas of interest in Representation (mathematics). In addition to Speech recognition research, the most cited papers aim to explore topics under Recurrent neural network, Word (computer architecture) and Decoding methods.

Papers citation over time

A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing at Spoken Language Technology Workshop (based on the number of publications) are:

• Dilek Hakkani-Tur (14 papers) published 5 papers at the last edition, 2 more than at the previous edition,
• Steve Young (8 papers) published 2 papers at the last edition, 1 less than at the previous edition,
• Gokhan Tur (8 papers) published 3 papers at the last edition, 1 more than at the previous edition,
• Giuseppe Riccardi (7 papers) published 1 paper at the last edition, 1 less than at the previous edition,
• Florian Metze (7 papers) published 4 papers at the last edition, 2 more than at the previous edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing at Spoken Language Technology Workshop (based on the number of publications) are:

• Microsoft (29 papers) published 12 papers at the last edition, 3 more than at the previous edition,
• Carnegie Mellon University (25 papers) published 8 papers at the last edition, 1 more than at the previous edition,
• IBM (12 papers) published 4 papers at the last edition, 2 more than at the previous edition,
• University of Washington (11 papers) published 3 papers at the last edition, 1 more than at the previous edition,
• University of Cambridge (11 papers) published 3 papers at the last edition, 1 less than at the previous edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2014 edition, 0.97% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 42.16% were posted by at least one author from the top 10 institutions publishing at the conference. Another 12.75% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 25.49% of all publications and 19.61% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.