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IWAENC 2022 : International Workshop on Acoustic Signal Enhancement

IWAENC 2022 : International Workshop on Acoustic Signal Enhancement

Bamberg , Germany

Submission Deadline: Friday 22 Apr 2022

Conference Dates: Sep 05, 2022 - Sep 05, 2022

Research
Impact Score 2.30

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Ranking & Metrics Impact Score is a novel metric devised to rank conferences based on the number of contributing the best scientists in addition to the h-index estimated from the scientific papers published by the best scientists. See more details on our methodology page.

Research Impact Score: 2.30
Contributing Best Scientists: 23
H5-index:
Papers published by Best Scientists 42
Research Ranking (Computer Science) 300

Conference Call for Papers

Topics
Acoustic echo and feedback suppression
Noise reduction
Microphone array processing
Source localization and tracking
Source separation
Dereverberation
Active noise control
Robot audition
Acoustic sensor networks
Acoustic event detection and scene classification
Modeling, analysis and synthesis of acoustic environments
Machine learning algorithms for acoustic signal processing
Auditory modeling and hearing instruments
Datasets for speech and audio
Speech intelligibility enhancement
Quality and intelligibility assessment
New and emerging topics in speech and audio processing

Overview

Top Research Topics at International Workshop on Acoustic Signal Enhancement?

  • Speech recognition (41.28%)
  • Acoustics (28.11%)
  • Algorithm (25.98%)

The conference mostly deals with topics like Speech recognition, Acoustics, Algorithm, Microphone and Speech enhancement. The research on Speech recognition featured in the conference combines topics in other fields like Reverberation, Signal-to-noise ratio, Noise measurement, Noise and Noise reduction. While the event focused on Reverberation, it was also able to explore topics like Estimator, Spectral density and Impulse response.

While Noise measurement is the focus of International Workshop on Acoustic Signal Enhancement, it also provided insights into the studies of Artificial neural network, Wiener filter, Artificial intelligence and Background noise. The presented Artificial intelligence research focuses mostly on Non-negative matrix factorization and, on occasion, topics in Pattern recognition. Acoustics research presented in the event encompasses a variety of subjects, including Microphone array, Noise-canceling microphone, Beamforming and Echo (computing).

Source separation is a focus of the presented Algorithm works and it dives deep in Source separation. In International Workshop on Acoustic Signal Enhancement, Direction of arrival and Robustness (computer science) are investigated in conjunction with one another to address concerns in Microphone research. Topics in Speech enhancement explored in International Workshop on Acoustic Signal Enhancement were investigated in conjunction with research in Intelligibility (communication), Voice activity detection and Speech coding.

What are the most cited papers published at the conference?

  • Multichannel audio database in various acoustic environments (133 citations)
  • Mmdenselstm: An Efficient Combination of Convolutional and Recurrent Neural Networks for Audio Source Separation (92 citations)
  • An improved non-intrusive intelligibility metric for noisy and reverberant speech (43 citations)

Research areas of the most cited articles at International Workshop on Acoustic Signal Enhancement:

The published papers are organized to reinforce research efforts on Speech recognition, Speech enhancement, Reverberation, Microphone array and Acoustics. The conference publications hold forums on Speech recognition that merge themes from other disciplines such as Artificial neural network, Noise measurement and Microphone. The featured Reverberation studies in the most cited articles mainly concentrate on Algorithm but also cover areas of interest in Time–frequency analysis, Cluster analysis and Joint (audio engineering).

What topics the last edition of the conference is best known for?

  • Artificial intelligence
  • Statistics
  • Algorithm

The previous edition focused in particular on these issues:

The primary areas of discussion in International Workshop on Acoustic Signal Enhancement are Speech recognition, Algorithm, Microphone, Speech enhancement and Artificial neural network. The event facilitates discussions on Speech recognition that incorporate concepts from other fields like Wideband, Signal-to-noise ratio, Estimator, Noise measurement and Convolutional neural network. The event explores issues in Algorithm which can be linked to other research areas like Sinusoidal model, Spectrogram, Blind signal separation and Time–frequency analysis.

While work presented in it provided substantial information on Microphone, it also covered topics in Acoustics, Reverberation, Noise and Direction of arrival. Speech enhancement research in International Workshop on Acoustic Signal Enhancement involves the investigation of Intelligibility (communication) studies, all of which are linked to disciplines such as Wiener filter. The featured Artificial neural network research is covered under the field of Artificial intelligence.

The most cited articles from the last conference are:

  • Mmdenselstm: An Efficient Combination of Convolutional and Recurrent Neural Networks for Audio Source Separation (92 citations)
  • Acoustic Scene Classification: An Overview of Dcase 2017 Challenge Entries (39 citations)
  • Phase Reconstruction with Learned Time-Frequency Representations for Single-Channel Speech Separation (28 citations)

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.

Research.com

The top authors publishing at International Workshop on Acoustic Signal Enhancement (based on the number of publications) are:

  • Simon Doclo (18 papers) published 6 papers at the last edition, 2 more than at the previous edition,
  • Emanuel A. P. Habets (16 papers) published 4 papers at the last edition, 1 less than at the previous edition,
  • Sharon Gannot (14 papers) published 3 papers at the last edition, 2 less than at the previous edition,
  • Patrick A. Naylor (13 papers) published 3 papers at the last edition, 2 less than at the previous edition,
  • Nobutaka Ono (11 papers) published 1 paper at the last edition, 5 less 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.

Research.com

Only papers with recognized affiliations are considered

The top affiliations publishing at International Workshop on Acoustic Signal Enhancement (based on the number of publications) are:

  • University of Oldenburg (21 papers) published 5 papers at the last edition, 1 more than at the previous edition,
  • Bar-Ilan University (14 papers) published 2 papers at the last edition, 3 less than at the previous edition,
  • University of Erlangen-Nuremberg (14 papers) published 7 papers at the last edition, 3 more than at the previous edition,
  • Nippon Telegraph and Telephone (13 papers) published 4 papers at the last edition the same number as at the previous edition,
  • Imperial College London (13 papers) published 3 papers at the last edition, 2 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.

Research.com

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.

Research.com

During the most recent 2018 edition, 7.02% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 34.91% were posted by at least one author from the top 10 institutions publishing at the conference. Another 19.81% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 24.53% of all publications and 20.75% 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.

Research.com

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.

Research.com

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).

Research.com

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

Research.com

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