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We are proposing a new approach to the solution of the cocktail party problem (CPP). The goal of the CPP is to isolate the speech signals of individuals who are concurrently talking while being recorded with a properly positioned microphone array. The new approach provides a powerful yet simple alternative to commonly used methods for the separation of(More)
In this paper we are presenting a method that provides a dramatic reduction in memory requirement and computational complexity for an inventory-style speech enhancement scheme with only a small impact on the perceptual quality of the output of the system. Inventory-style or corpus-based speech enhancement generally attempts to generate a clean speech signal(More)
We present a new method for the enhancement of speech. The method is designed for scenarios in which targeted speaker enrollment as well as system training within the typical noise environment are feasible. The proposed procedure is fundamentally different from most conventional and state-of-the-art denoising approaches. Instead of filtering a distorted(More)
We present a new approach for corpus-based speech enhancement that significantly improves over a method published by Xiao and Nickel in 2010. Corpus-based enhancement systems do not merely filter an incoming noisy signal, but resynthesize its speech content via an inventory of pre-recorded clean signals. The goal of the procedure is to perceptually improve(More)
We are presenting a method for the enhancement of speech in speaker dedicated speech communication systems. The proposed procedure is fundamentally different from most state-of-the-art filtering approaches. Instead of filtering a distorted signal we are re-synthesizing a new “clean” signal based on its likely characteristics. These(More)
We present a new method for inventory-style speech enhancement that significantly improves over earlier approaches [1]. Inventory-style enhancement attempts to resynthesize a clean speech signal from a noisy signal via corpus-based speech synthesis. The advantage of such an approach is that one is not bound to trade noise suppression against signal(More)
We are presenting a new speech waveform inventory based approach for the denoising of speech. The method combines an inventory style parametric description of speech signals with a statistical analysis of the underlying parameter space in clean and noisy conditions. Sufficient parameter statistics for successful denoising can be learned from around 40(More)
We are presenting a new approach for blind multichannel system identification. The approach relies on the existence of so called exclusive activity periods (EAPs) in the source signals. EAPs are time intervals during which only one source is active and all other sources are inactive (i.e. zero). The existence of EAPs is not guaranteed for arbitrary signal(More)
We propose a new method for noise robust encoding of speech at very low bit rates. The method constitutes an extension to common speech-recognition/speech-resynthesis schemes, which have become feasible in recent years due to advances in speech recognition and artificial speech synthesis. Most such methods, however, suffer from a significant performance(More)