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A. Biswas

4 papers hereh-index 6141 citations24 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • eess.AS4
same name
  • A. Biswas — 22 papers, h 18
  • A. Biswas — 16 papers, h 34
  • A. Biswas — 14 papers, h 41
  • A. Biswas — 11 papers
  • A. Biswas — 10 papers, h 15
  • A. Biswas — 9 papers, h 24

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192022
most citedAudio Codec Enhancement with Generative Adversarial Networks

2 citations · 4 across the 4 of their papers we have counts for

collaborators
Showing eess.ASShow all

4 papers · 1 filter

eess.AS2022

Stereo InSE-NET: Stereo Audio Quality Predictor Transfer Learned from Mono InSE-NET

Arijit Biswas, Guanxin Jiang

Automatic coded audio quality predictors are typically designed for evaluating single channels without considering any spatial aspects. With InSE-NET [1], we demonstrated mimicking…

eess.AS2021★ 2 cited

InSE-NET: A Perceptually Coded Audio Quality Model based on CNN

Guanxin Jiang, Arijit Biswas, Christian Bergler +1

Automatic coded audio quality assessment is an important task whose progress is hampered by the scarcity of human annotations, poor generalization to unseen codecs, bitrates, conte…

eess.AS2020★ 2 cited

Audio Codec Enhancement with Generative Adversarial Networks

Arijit Biswas, Dai Jia

Audio codecs are typically transform-domain based and efficiently code stationary audio signals, but they struggle with speech and signals containing dense transient events such as…

eess.AS2019

Analysis by Adversarial Synthesis -- A Novel Approach for Speech Vocoding

Ahmed Mustafa, Arijit Biswas, Christian Bergler +2

Classical parametric speech coding techniques provide a compact representation for speech signals. This affords a very low transmission rate but with a reduced perceptual quality o…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.