This paper discusses the application of noise reduction algorithms for dual-microphone mobile phones. An analysis of the acoustical environment based on recordings with a dual-microphone mock-up phone mounted on a dummy head is given. Motivated by the recordings, a novel dual-channel noise reduction algorithm is proposed.The key components are a noise PSD estimator and an improved spectral weighting rule which both explicitly exploit the Power Level Differences (PLD) of the desired speech signal between the microphones. Experiments with recorded data show that this low complexity system has a good performance and is bene cial for an integration into future mobile communication devices.
This contribution presents an efficient technique for the enhancement of speech signals disturbed by wind noise. In almost all noise reduction systems an estimate of the current noise power spectral density (PSD) is required. As common methods for background noise estimation fail due to the non-stationary characteristics of wind noise signals, special algorithms are required. The proposed estimation technique consists of three steps: a feature extraction followed by a wind noise detection and the calculation of the current wind noise PSD. For all steps we exploit the different spectral energy distributions of speech and wind noise. In this context, the so-called signal centroids are introduced. Investigations with measured audio data show that our method can cope with the non-stationary characteristics and enables a sufficient reduction of wind noise. In contrast to other wind noise reduction schemes the proposed algorithm has low complexity and low memory consumption.
In this contribution, we study the characteristics of sound generated by wind and a signal model for the synthesis of wind noise signals is derived. An analysis of the statistics of wind noise recorded in a laboratory setup is carried out with respect to the spectral and temporal properties of the signals. In particular, an autoregresive model is developed for the spectral shape description and the temporal statistics are modeled by a Markov chain. These two components are combined in a model which synthesizes reproducible artificial wind noise signals. Furthermore, a database of measured wind noise signals is provided. The aim of this model and the measured audio data is to provide wind signals for the evaluation of speech enhancement and noise reduction systems.Index Terms-Wind noise analysis, wind noise simulation, communication quality assessment, wind noise database
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.