Robert Aichner

Signal Processing · 2020–2023

A researcher in the Science corpus: 7 papers; trusts 13 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Signal Processing — 108 citations into it; #4,138 of 7,572 by trust here, #1,904 by citations
• Artificial Intelligence — 56 citations into it; #25,860 of 35,345 by trust here, #18,586 by citations
• Speech & Audio — 33 citations into it; #1,029 of 1,076 by trust here, #980 by citations
• Computational Mechanics — 32 citations into it
• Cognitive Neuroscience — 30 citations into it
• Biomedical Engineering — 10 citations into it; #7,773 of 10,734 by trust here, #4,948 by citations
• Electrical and Electronic Engineering — 7 citations into it

Whom Robert Aichner trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Chandan K. A. Reddy
2. Babak Naderi

Who trusts Robert Aichner overall

1. Ross Cutler
2. Babak Naderi
3. Vishak Gopal
4. Hubert Siuzdak
5. Chandan K. A. Reddy

Papers from Robert Aichner's perspective

Ordered by how strongly the researchers Robert Aichner trusts endorse each paper. Same corpus, a different order for every researcher.

1. Audio Set: An ontology and human-labeled dataset for audio events
2. Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs
3. VoxCeleb2: Deep Speaker Recognition
4. X-Vectors: Robust DNN Embeddings for Speaker Recognition
5. Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation
6. A Regression Approach to Speech Enhancement Based on Deep Neural Networks
7. A study on data augmentation of reverberant speech for robust speech recognition
8. The Diverse Environments Multi-channel Acoustic Noise Database (DEMAND): A database of multichannel environmental noise recordings
9. Image method for efficiently simulating small‐room acoustics
10. A Hybrid DSP/Deep Learning Approach to Real-Time Full-Band Speech Enhancement

Their papers

• The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Testing Framework, and Challenge Results (2020) — 460 citations
• ICASSP 2022 Acoustic Echo Cancellation Challenge (2022) — 81 citations
• Interspeech 2021 Deep Noise Suppression Challenge (2021) — 206 citations
• Icassp 2022 Deep Noise Suppression Challenge (2022) — 237 citations
• ICASSP 2023 Deep Noise Suppression Challenge (2023) — 193 citations
• ICASSP 2021 Deep Noise Suppression Challenge (2020) — 161 citations
• The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Speech Quality and Testing Framework (2020) — 91 citations