Noise

About: Noise is a research topic. Over the lifetime, 5111 publications have been published within this topic receiving 69407 citations. The topic is also known as: Мопсы танцуют под радио бандитов из сталкера 10 часов.

Indexing based on time-variant transforms of an audio signal's spectrogram

Abstract: An audio identification system generates audio fingerprints and indexes associated with the audio fingerprints based on discrete and overlapping frames within a sample of an audio signal. The system applies a time-to-frequency domain transform to a time-sequence of frames, which may be filtered. The audio identification system then applies a time-variant transformation (e.g., a Discrete Cosine Transform) to the transformed frames and generates an audio fingerprint and index by selecting sets of coefficients of the time-variant transformation. The system selects coefficients that are less sensitive to possible noise and/or distortions in the underlying signal, such as low-frequency coefficients. The time-variant transformation provides sufficient sampling among the indexes by incorporating the phase information of the frames into the indexes. The system stores the audio fingerprint and other identifying information by index for efficient retrieval and matching of the retrieved fingerprints.

Noise reduction using a small-scale microphone array in multi noise source environment

Abstract: To construct a front-end for ASR systems using a small-scale microphone array in real environments, robustness for unstable sudden-noises, multi-noises and near-field sound sources are required. This paper proposes a front-end method for enhancing target signals that subtracts estimated noise from noisy signals by using paired microphones in each sub-band. The proposed method assumes one integrated noise source exists in each narrow sub-band, estimates its noise spectrum correctly using the cancellation method, and subtracts it from the noise-added sound spectrum using the SS. Thus, the proposed method can be used in multi noise source and near-field conditions, although it uses a small-scale microphone array consisting of only three microphones.

Effect of Noise Intensity and Illumination Intensity on Visual Performance

Abstract: The results of Experiment 1 indicated that noise and illumination intensity have a significant effect on character identification performance, which was better at 30 dBA than at 60 and 90 dBA, and better at 500 and 800 lux than at 200 lux. However, the interaction of noise and illumination intensity did not significantly affect visual performance. The results of Experiment 2 indicated that noise and illumination intensity also had a significant effect on reading comprehension performance, which was better at 30 dBA than at 60 and 90 dBA, and better at 500 lux than at 200 and 800 lux. Furthermore, reading comprehension performance was better at 500 lux lighting and 30 dBA noise than with 800 lux and 90 dBA. High noise intensity impaired visual performance, and visual performance at normal illumination intensity was better than at other illumination intensities. The interaction of noise and illumination had a significant effect on reading comprehension. These results indicate that noise intensity lower than 30 dBA and illumination intensity approximately 500 lux might be the optimal conditions for visual work.

Robust treatment of impulsive noise in speech and audio signals

Abstract: Markov chain Monte Carlo methods are presented for treatment of localized, impulsive noise (outliers) in digitized waveforms, within a Bayesian hierarchical framework. Outliers in audio signals occur as`clicks' and`crackles' in degraded sound recordings and impulsive noise in communications channels. Sampling-based methods for detection and correction of such artefacts are presented, in which individual noise sources are modelled as Gaussian with unknown scale, allowing for robustness to heavy-tailed noise distributions. Results are presented for speech and audio signals obtained from digitized sound recordings.