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Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 7 Similar Profiles
Speech intelligibility Engineering & Materials Science
Speech enhancement Engineering & Materials Science
intelligibility Physics & Astronomy
Mean square error Engineering & Materials Science
augmentation Physics & Astronomy
estimators Physics & Astronomy
envelopes Physics & Astronomy
education Physics & Astronomy

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Research Output 2016 2019

  • 4 Article in proceeding
  • 3 Journal article
  • 1 Ph.D. thesis
Speech intelligibility
Speech enhancement
intelligibility
Mean square error
augmentation
4 Citations (Scopus)

Monaural Speech Enhancement using Deep Neural Networks by Maximizing a Short-Time Objective Intelligibility Measure

Kolbæk, M., Tan, Z-H. & Jensen, J., 2018, International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, p. 5059-5063 (I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings).

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Single-Microphone Speech Enhancement and Separation Using Deep Learning

Kolbæk, M., 2018, Aalborg Universitetsforlag. 233 p. (Ph.d.-serien for Det Tekniske Fakultet for IT og Design, Aalborg Universitet).

Research output: Book/ReportPh.D. thesisResearch

Open Access
File
7 Citations (Scopus)

Joint separation and denoising of noisy multi-talker speech using recurrent neural networks and permutation invariant training

Kolbæk, M., Yu, D., Tan, Z-H. & Jensen, J., 2017, International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, 6 p. (IEEE International Workshop on Machine Learning for Signal Processing (MLSP). Proceedings.).

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

44 Citations (Scopus)

Multitalker Speech Separation With Utterance-Level Permutation Invariant Training of Deep Recurrent Neural Networks

Kolbæk, M., Yu, D., Tan, Z-H. & Jensen, J., 13 Jul 2017, In : I E E E Transactions on Audio, Speech and Language Processing. 25, 10, p. 1901-1913 13 p.

Research output: Contribution to journalJournal articleResearchpeer-review

Activities 2018 2018

  • 1 Internal examination

Single-Microphone Speech Enhancement and Separation Using Deep Learning

Thomas Arildsen (Opponent)
30 Nov 2018

Activity: ExaminationInternal examination

Press / Media

Kunstige neurale netværk skal gøre livet lettere for høreapparatbrugere

Morten Kolbæk, Jesper Jensen & Zheng-Hua Tan

04/01/201907/01/2019

17 items of media coverage, 1 media contribution

Press/Media: Press / Media