Romain Serizel

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In this paper we study the use of unsupervised feature learning for acoustic scene classification (ASC). The acoustic environment recordings are represented by time-frequency images from which we learn features in an unsupervised manner. After a set of preprocessing and pooling steps, the images are decomposed using matrix factorization methods. By(More)
Most of digital signal processing applications are specified and designed with floatingpoint arithmetic but are finally implemented using fixed-point architectures. Thus, the design flow requires a floating-point to fixed-point conversion stage which optimizes the implementation cost under execution time and accuracy constraints. This accuracy constraint is(More)
This paper presents low-rank approximation based multichannel Wiener filter algorithms for noise reduction in speech plus noise scenarios, with application in cochlear implants. In a single speech source scenario, the frequency-domain autocorrelation matrix of the speech signal is often assumed to be a rank-1 matrix, which then allows to derive different(More)
This paper presents combined active noise control and noise reduction schemes for hearing aids to tackle secondary path effects and effects of noise leakage through an open fitting. While such leakage contributions and the secondary acoustic path from the loudspeaker to the tympanic membrane are usually not taken into account in standard noise reduction(More)
This paper presents multichannel Wiener filtering-based algorithms for noise reduction in cochlear implants. In a single speech scenario, the autocorrelation matrix of the speech signal can be approximated by a rank-1 matrix. It is then possible to derive noise reduction filters that deliver improved signal-to-noise ratio performance. The link between these(More)
This paper focuses on speech enhancement in hearing aids and presents an integrated approach to active noise control and noise reduction which is based on an optimization over a zone-of-quiet generated by the active noise control. A basic integrated active noise control and noise reduction scheme has been introduced previously to tackle secondary path(More)
This paper analyses the output signal-to-noise ratio for a standard noise reduction scheme and for an integrated active noise control and noise reduction scheme, both applied in the hearing aid framework including the effects of signal leakage through an open fitting and secondary path effects. In particular, a standard noise reduction scheme based on the(More)
This paper introduces deep neural network (DNN) hidden Markov model (HMM) based methods to tackle speech recognition in heterogeneous groups of speakers including children. We target three speaker groups consisting of children, adult males and adult females. Two different kinds of approaches are introduced here: approaches based on DNN adaptation and(More)