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- Kris Hermus, Patrick Wambacq, Hugo Van hamme
- EURASIP J. Adv. Sig. Proc.
- 2007

The objective of this paper is threefold: (1) to provide an extensive review of signal subspace speech enhancement, (2) to derive an upper bound for the performance of these techniques, and (3) to present a comprehensive study of the potential of subspace filtering to increase the robustness of automatic speech recognisers against stationary additive noiseâ€¦ (More)

- Kris Hermus, Werner Verhelst, Philippe Lemmerling, Patrick Wambacq, Sabine Van Huffel
- Signal Processing
- 2005

This paper presents the derivation of a new perceptual model that represents speech and audio signals by a sum of exponentially damped sinusoids. Compared to a traditional sinusoidal model, the exponential sinusoidal model (ESM) is better suited to model transient segments that are readily found in audio signals. Total least squares (TLS) algorithms areâ€¦ (More)

- Kris Hermus, Hugo Van hamme, Sufian Irhimeh
- IEEE Signal Processing Letters
- 2007

We present a new algorithm for the estimation of the voicing cut-off frequency (VCO), i.e., the frequency that separates the harmonic low-frequency part from the aperiodic high-frequency part in voiced speech. The VCO is estimated as the frequency for which the sum of the harmonicity scores of all pitch harmonics below that frequency is maximized. Theâ€¦ (More)

- Kris Hermus, Werner Verhelst, Patrick Wambacq
- 2002 IEEE International Conference on Acousticsâ€¦
- 2002

While a traditional sinusoidal model is capable of representing audio segments, a sum of exponentially damped sinusoids is more efficient to model the transient segments that are readily found in audio signals. In this paper, Total Least Squares (TLS) algorithms are applied to automatically extract the modeling parameters in the Exponential Sinusoidal Modelâ€¦ (More)

- Kris Hermus, Ioannis Dologlou, Patrick Wambacq, Dirk Van Compernolle
- EUROSPEECH
- 1999

This paper presents a new approach to improve the robustness of large vocabulary continuous speech recognition. The proposed technique { based on Singular Value Decomposition (SVD) { originates from classical signal enhancement, but it is adapted to the speci c requirements imposed by the speech recognition process. Additive noise reduction is obtained byâ€¦ (More)

- Kris Hermus, Laurent Girin, Hugo Van hamme, Sufian Irhimeh
- 2008 IEEE International Conference on Acousticsâ€¦
- 2008

We present a new algorithm for the automatic estimation of the voicing cut-off frequency (VCO), i.e., the frequency that separates the periodic low-frequency part from the aperiodic high-frequency part in voiced segments of natural speech. Starting from the power spectrum of a two pitch period speech frame, we define the VCO to be located at the frequencyâ€¦ (More)

- Kris Hermus, Werner Verhelst, Patrick Wambacq, Philippe Lemmerling
- INTERSPEECH
- 2000

We describe how Total Least Squares (TLS) algorithms can be applied as a powerful and eÃ†cient modelling tool for wideband speech. A detailed description in both time domain and frequency domain illustrates how the modelling functions { damped sinusoids { naturally synthesise non-stationary signals. Straightforward implementations of TLS applied to fullbandâ€¦ (More)

- Kris Hermus, Werner Verhelst, Patrick Wambacq
- INTERSPEECH
- 2000

Signal Subspace (SS) based speech enhancement techniques obtain signi cant additive-noise reduction by altering the singular value spectrum of the speech observation matrix. Among the class of di erent possible SS weighting strategies, the Minimum Variance (MV) estimation method substantially increases the speech recognition accuracy in additive noiseâ€¦ (More)

- Kris Hermus, Hugo Van hamme, Werner Verhelst, Sufian Irhimeh, Jan De Moortel
- 2007 IEEE International Conference on Acousticsâ€¦
- 2007

We present a harmonic-plus-noise modelling (HNM) strategy in the context of corpus-based text-to-speech (TTS) synthesis, in which whole speech phonemes are modelled in their integrity, contrary to the traditional frame-based approach. The pitch and amplitude trajectories of each phoneme are modelled with a low-order DCT expansion. The parameter analysisâ€¦ (More)

Most parametric audio coders use a traditional sinusoidal model to represent the tonal parts of audio signals, together with dedicated models for the noise and transient-like parts of the audio signal. In this paper we apply Total Least Squares (TLS) algorithms to automatically extract the modeling parameters of a Exponential Sinusoidal Model (ESM) forâ€¦ (More)