Simon Graf

Simon Graf
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Main area of research
Speech enhancement

Simon Graf is a PhD researcher at the speech enhancement group in Ulm, Germany. He is registered as a PhD student at the Kiel University, Kiel, Germany. The topic of his research is Robust Voice Activity Detection for Non-Stationary Background Noise. The scope of his work includes feature extraction and classification for voice activity detection.

Selected articles

Detection of Voiced Speech and Pitch Estimation for Applications with Low Spectral Resolution

Speech enhancement algorithms are employed in many applications, such as hands-free telephones, or speech recognizers, to recover a speech signal that is recorded in a

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Voice Activity Detection Based on Modulation-Phase Differences

Many speech processing algorithms rely on voice activity detection (VAD) that separates speech from noise. For this task, several features have been introduced that employ

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Kurtosis-Controlled Babble Noise Suppression

When a speech application is employed in a crowded environment, the user’s voice superposes with many interfering voices. This babble noise is a challenge for

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Features for voice activity detection: a comparative analysis

In many speech signal processing applications, voice activity detection (VAD) plays an essential role for separating an audio stream into time intervals that contain speech

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Listening Test to Determine the Mismatch Between Signal-to-Noise Ratio and Human Perception

Evaluations of speech enhancement systems are typically based on artificially generated noisy speech signals. A common approach to quantify the weighting of speech and background

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