A Corpus-Based Approach to Speech Enhancement from Nonstationary Noise

Temporal dynamics and speaker characteristics are two important features of speech that distinguish speech from noise. In this paper, we propose a method to maximally extract these two features of speech for speech enhancement. We demonstrate that this can reduce the requirement for prior information about the noise, which can be difficult to estimate for fast-varying noise. Given noisy speech, the new approach estimates clean speech by recognizing long segments of the clean speech as whole units. In the recognition, clean speech sentences, taken from a speech corpus, are used as examples. Matching segments are identified between the noisy sentence and the corpus sentences. The estimate is formed by using the longest matching segments found in the corpus sentences. Longer speech segments as whole units contain more distinct dynamics and richer speaker characteristics, and can be identified more accurately from noise than shorter speech segments. Therefore, estimation based on the longest recognized segments increases the noise immunity and hence the estimation accuracy. The new approach consists of a statistical model to represent up to sentence-long temporal dynamics in the corpus speech, and an algorithm to identify the longest matching segments between the noisy sentence and the corpus sentences. The algorithm is made more robust to noise uncertainty by introducing missing-feature based noise compensation into the corpus sentences. Experiments have been conducted on the TIMIT database for speech enhancement from various types of nonstationary noise including song, music, and crosstalk speech. The new approach has shown improved performance over conventional enhancement algorithms in both objective and subjective evaluations.

A calming cacophony: Social identity can shape the experience of loud noise

Environmental Psychology has typically considered noise as pollution and focused upon its negative impact. However, recent research in psychology and anthropology indicates the experience of noise as aversive depends upon the meanings with which it is attributed. Moreover, such meanings seem to be dependent on the social context. Here we extend this research through studying the aural experience of a religious festival in North India which is characterised by loud, continuous and cacophonous noise. Reporting an experiment and semi-structured interviews, we show that loud noise is experienced as pleasant or unpleasant according to the meanings attributed to it. Specifically, the experiment shows the same noise is experienced more positively (and listened to longer) when attributed to the festival rather than to a non-festival source. In turn, the qualitative data show that within the Mela, noises judged as having a religious quality are reported as more positive than noises that are not. Moreover, the qualitative data suggest a key factor in the evaluation of noise is our participants’ social identities as pilgrims. This identity provides a framework for interpreting the auditory environment and noises judged as intruding into their religious experience were judged negatively, whereas noises judged as contributing to their religious experience were judged more positively. Our findings therefore point to the ways in which our social identities are implicated in the process of attributing meaning to the auditory environment.

Rapid formation of robust auditory memories: Insights from noise

Before a natural sound can be recognized, an auditory signature of its source must be learned through experience. Here we used random waveforms to probe the formation of new memories for arbitrary complex sounds. A behavioral measure was designed, based on the detection of repetitions embedded in noises up to 4 s long. Unbeknownst to listeners, some noise samples reoccurred randomly throughout an experimental block. Results showed that repeated exposure induced learning for otherwise totally unpredictable and meaningless sounds. The learning was unsupervised and resilient to interference from other task-relevant noises. When memories were formed, they emerged rapidly, performance became abruptly near-perfect, and multiple noises were remembered for several weeks. The acoustic transformations to which recall was tolerant suggest that the learned features were local in time. We propose that rapid sensory plasticity could explain how the auditory brain creates useful memories from the ever-changing, but sometimes repeating, acoustical world. © 2010 Elsevier Inc.

The detection of repetitions in noise before and after perceptual learning.

In noise repetition-detection tasks, listeners have to distinguish trials of continuously running noise from trials in which noise tokens are repeated in a cyclic manner. Recently, it has been shown that using the exact same noise token across several trials (“reference noise”) facilitates the detection of repetitions for this token [Agus et al. (2010). Neuron 66, 610–618]. This was attributed to perceptual learning. Here, the nature of the learning was investigated. In experiment 1, reference noise tokens were embedded in trials with or without cyclic presentation. Naïve listeners reported repetitions in both cases, thus responding to the reference noise even in the absence of an actual repetition. Experiment 2, with the same listeners, showed a similar pattern of results even after the design of the experiment was made explicit, ruling out a misunderstanding of the task. Finally, in experiment 3, listeners reported repetitions in trials containing the reference noise, even before ever hearing it presented cyclically. The results show that listeners were able to learn and recognize noise tokens in the absence of an immediate repetition. Moreover, the learning mandatorily interfered with listeners' ability to detect repetitions. It is concluded that salient perceptual changes accompany the learning of noise.

Noise Quartet

Performance at the International Computer Music Conference, University of Huddersfield (with Eric Lyon, Franziska Schroder & Steve Davis).

Rethinking Local Government Support for Youth Arts:The Case of NOISE South Dublin

Within Ireland, interest in strategically supporting young people’s participation in the arts has increased. Additionally, awareness of the Internet’s potential for promot- ing engagement with the arts has grown. Addressing national directives and local needs assessments, South Dublin County Council’s Arts Office initiated NOISE South Dublin (http://www.noisesouthdublin.com), an interactive Web site based on Australia Council’s NOISE project (http://www.noise.net), to promote the creative development of young people in the county. This article presents the practical chal- lenges and potential of youth arts Web-based programs for harnessing the creative engagement of youth. It concludes that the Internet is only useful if it expands online engagement offline.

Adaptive Fusion Of Particle Filtering And Spatio-Temporal Motion Energy For Human Tracking

Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.

Vibration based seismic damage identification procedure for a steel concentrically braced frame structure

An approach for seismic damage identification of a single-storey steel concentrically braced frame (CBF) structure is presented through filtering and double integration of a recorded acceleration signal. A band-pass filter removes noise from the acceleration signal followed by baseline correction being used to reduce the drift in velocity and displacement during numerical integration. The pre-processing achieves reliable numerical integration that predicts the displacement response accurately when compared to the measured lateral in-plane displacement of the CBF structure. The lateral displacement of the CBF structure is used to infer buckling and yielding of bracing members through seismic tests. The level of interstorey drift of the CBF during a seismic excitation allows the yield and buckling of the bracing members to be identified and indirectly detects damage based on exceedance of calculated displacement limits. The calculated buckling and yielding displacement threshold limits used to identify damage are demonstrated to accurately identify initial buckling and yielding in the bracing members.

Frequency Filtering of Torsional Alfvén Waves by Chromospheric Magnetic Field

In this Letter, we demonstrate how the observation of broadband frequency propagating torsional Alfvén waves in chromospheric magnetic flux tubes can provide valuable insight into their magnetic field structure. By implementing a full nonlinear three-dimensional magnetohydrodynamic numerical simulation with a realistic vortex driver, we demonstrate how the plasma structure of chromospheric magnetic flux tubes can act as a spatially dependent frequency filter for torsional Alfvén waves. Importantly, for solar magnetoseismology applications, this frequency filtering is found to be strongly dependent on magnetic field structure. With reference to an observational case study of propagating torsional Alfvén waves using spectroscopic data from the Swedish Solar Telescope, we demonstrate how the observed two-dimensional spatial distribution of maximum power Fourier frequency shows a strong correlation with our forward model. This opens the possibility of beginning an era of chromospheric magnetoseismology, to complement the more traditional methods of mapping the magnetic field structure of the solar chromosphere.

Understanding Astrophysical Noise from Stellar Surface Magneto-Convection

To obtain cm/s precision, stellar surface magneto-convection must be disentangled from observed radial velocities (RVs). In order to understand and remove the convective signature, we create Sun-as-a-star model observations based on a 3D magnetohydrodynamic solar simulation. From these Sun-as-a-star model observations, we find several line characteristics are correlated with the induced RV shifts. The aim of this campaign is to feed directly into future high precision RV studies, such as the search for habitable, rocky worlds, with forthcoming spectrographs such as ESPRESSO.

Systolic two-port adaptor for high performance wave digital filtering

The authors present a VLSI circuit for implementing wave digital filter (WDF) two-port adaptors. Considerable speedups over conventional designs have been obtained using fine grained pipelining. This has been achieved through the use of most significant bit (MSB) first carry-save arithmetic, which allows systems to be designed in which latency L is small and independent of either coefficient or input data wordlength. L is determined by the online delay associated with the computation required at each node in the circuit (in this case a multiply/add plus two separate additions). This in turn means that pipelining can be used to considerably enhance the sampling rate of a recursive digital filter. The level of pipelining which will offer enhancement is determined by L and is fine-grained rather than bit level. In the case of the circuit considered, L = 3. For this reason pipeline delays (half latches) have been introduced between every two rows of cells to produce a system with a once every cycle sample rate.