Intermediate Signal-to-noise Ratio Research Articles

The Impact of Temporally Coherent Visual Cues on Speech Perception in Complex Auditory Environments.

Speech perception often takes place in noisy environments, where multiple auditory signals compete with one another. The addition of visual cues such as talkers’ faces or lip movements to an auditory signal can help improve the intelligibility of speech in those suboptimal listening environments. This is referred to as audiovisual benefits. The current study aimed to delineate the signal-to-noise ratio (SNR) conditions under which visual presentations of the acoustic amplitude envelopes have their most significant impact on speech perception. Seventeen adults with normal hearing were recruited. Participants were presented with spoken sentences in babble noise either in auditory-only or auditory-visual conditions with various SNRs at −7, −5, −3, −1, and 1 dB. The visual stimulus applied in this study was a sphere that varied in size syncing with the amplitude envelope of the target speech signals. Participants were asked to transcribe the sentences they heard. Results showed that a significant improvement in accuracy in the auditory-visual condition versus the audio-only condition was obtained at the SNRs of −3 and −1 dB, but no improvement was observed in other SNRs. These results showed that dynamic temporal visual information can benefit speech perception in noise, and the optimal facilitative effects of visual amplitude envelope can be observed under an intermediate SNR range.

Cognitive Interference Alignment Schemes for IoT Oriented Heterogeneous Two-Tier Networks.

This paper considers interference management and capacity improvement for Internet of Things (IoT) oriented two-tier networks by exploiting cognition between network tiers with interference alignment (IA). More specifically, we target our efforts on the next generation two-tier networks, where a tier of femtocell serving multiple IoT devices shares the licensed spectrum with a tier of pre-existing macrocell via a cognitive radio. Aiming to manage the cross-tier interference caused by cognitive spectrum sharing as well as ensure an optimal capacity of the femtocell, two novel self-organizing cognitive IA schemes are proposed. First, we propose an interference nulling based cognitive IA scheme. In such a scheme, both co-tier and cross-tier interferences are aligned into the orthogonal subspace at each IoT receiver, which means all the interference can be perfectly eliminated without causing any performance degradation on the macrocell. However, it is known that the interference nulling based IA algorithm achieves its optimum only in high signal to noise ratio (SNR) scenarios, where the noise power is negligible. Consequently, when the imposed interference-free constraint on the femtocell can be relaxed, we also present a partial cognitive IA scheme that further enhances the network performance under a low and intermediate SNR. Additionally, the feasibility conditions and capacity analyses of the proposed schemes are provided. Both theoretical and numerical results demonstrate that the proposed cognitive IA schemes outperform the traditional orthogonal precoding methods in terms of network capacity, while preserving for macrocell users the desired quality of service.

Toward a more comprehensive understanding of the impact of masker type and signal-to-noise ratio on the pupillary response while performing a speech-in-noise test

Difficulties arising in everyday speech communication often result from the acoustical environment, which may contain interfering background noise or competing speakers. Thus, listening and understanding speech in noise can be exhausting. Two experiments are presented in the current study that further explored the impact of masker type and Signal-to-Noise Ratio (SNR) on listening effort by means of pupillometry. In both studies, pupillary responses of participants were measured while performing the Danish Hearing in Noise Test (HINT; Nielsen and Dau, 2011). The first experiment aimed to replicate and extend earlier observed effects of noise type and semantic interference on listening effort (Koelewijn et al., 2012). The impact of three different masker types, i.e. a fluctuating noise, a 1-talker masker and a 4-talker masker on listening effort was examined at a fixed speech intelligibility. In a second experiment, effects of SNR on listening effort were examined while presenting the HINT sentences across a broad range of fixed SNRs corresponding to intelligibility scores ranging from 100% to 0% correct performance. A peak pupil dilation (PPD) was calculated and a Growth Curve Analysis (GCA) was performed to examine listening effort involved in speech recognition as a function of SNR. The results of two experiments showed that the pupil dilation response is highly affected by both masker type and SNR when performing the HINT. The PPD was highest, suggesting the highest level of effort, for speech recognition in the presence of the 1-talker masker in comparison to the 4-talker babble and the fluctuating noise masker. However, the disrupting effect of one competing talker disappeared for intelligibly levels around 50%. Furthermore, it was demonstrated that the pupillary response strongly varied as a function of SNRs. Listening effort was highest for intermediate SNRs with performance accuracies ranging between 30% and 70% correct. GCA revealed time-dependent effects of the SNR on the pupillary response that were not reflected in the PPD.

Psychometric Functions of Dual-Task Paradigms for Measuring Listening Effort.

The purpose of the study was to characterize the psychometric functions that describe task performance in dual-task listening effort measures as a function of signal to noise ratio (SNR). Younger adults with normal hearing (YNH, n = 24; experiment 1) and older adults with hearing impairment (n = 24; experiment 2) were recruited. Dual-task paradigms wherein the participants performed a primary speech recognition task simultaneously with a secondary task were conducted at a wide range of SNRs. Two different secondary tasks were used: an easy task (i.e., a simple visual reaction-time task) and a hard task (i.e., the incongruent Stroop test). The reaction time (RT) quantified the performance of the secondary task. For both participant groups and for both easy and hard secondary tasks, the curves that described the RT as a function of SNR were peak shaped. The RT increased as SNR changed from favorable to intermediate SNRs, and then decreased as SNRs moved from intermediate to unfavorable SNRs. The RT reached its peak (longest time) at the SNRs at which the participants could understand 30 to 50% of the speech. In experiments 1 and 2, the dual-task trials that had the same SNR were conducted in one block. To determine if the peak shape of the RT curves was specific to the blocked SNR presentation order used in these experiments, YNH participants were recruited (n = 25; experiment 3) and dual-task measures, wherein the SNR was varied from trial to trial (i.e., nonblocked), were conducted. The results indicated that, similar to the first two experiments, the RT curves had a peak shape. Secondary task performance was poorer at the intermediate SNRs than at the favorable and unfavorable SNRs. This pattern was observed for both YNH and older adults with hearing impairment participants and was not affected by either task type (easy or hard secondary task) or SNR presentation order (blocked or nonblocked). The shorter RT at the unfavorable SNRs (speech intelligibility < 30%) possibly reflects that the participants experienced cognitive overload and/or disengaged themselves from the listening task. The implication of using the dual-task paradigm as a listening effort measure is discussed.

Multi-Target Detection using Total Correlation for Noise Radar Systems

Target detection is one of the important functions of radar systems. In this paper, we present a detection method using total correlation (TC) based on information theory for noise radar systems which enables the detection of multiple targets at intermediate and low signal-to-noise ratio (SNR) regimes. The proposed method utilizes the largest eigenvalue of the sample covariance matrix to extract information from the transmitted signal replica, and outperforms the conventional TC detector when reflected signals have intermediate or low SNR values. Additionally, in order to avoid ambiguous target occurrence, we propose an adaptive threshold to guarantee the detection performance with the same receiving antenna elements for a given false alarm probability. The threshold is computed from the largest and smallest eigenvalue distributions based on random matrix theory. Simulations show that the proposed detection method can be used for a wide range of SNR environments, and the threshold provides definitive target detection.

Partially coherent light-emitting diode illumination for video-rate in-line holographic microscopy

The light of a light-emitting diode or a common thermal source, such as a tungsten filament lamp, is known to be quasi-incoherent. We generated partially coherent light of these sources with a volume of coherence in the micrometer range of 5-100 μm3 by spatial and spectral filtering. The corresponding degree of partial coherence was adapted for microscopic interference setups, such as a digital in-line holographic microscope. The practicability of the sources was determined by the spectral emittance and the resulting signal-to-noise ratio (SNR) of the detector. The microscale coherence in correlation with the SNR and its resolution for microscopy were analyzed. We demonstrate how low-light-level, non-laser sources enable holographic imaging with a video frame rate (25 frames/s), an intermediate SNR of 8 dB, and a volume of coherence of 3.4×10(4) μm3. Holograms of objects with a lateral resolution of 1 μm were achieved using a microscope lens (50×/NA=0.7) and a CCD camera featuring a 4-12 bit dynamic range.

Trellis and Convolutional Precoding for Transmitter- Based Interference Presubtraction

This paper studies the combination of practical trellis and convolution codes with Tomlinson-Harashima precoding (THP) for the presubtraction of multiuser interference that is known at the transmitter but not known at the receiver. It is well known that a straightforward application of THP suffers power, modulo, and shaping losses. This paper proposes generalizations of THP that recover some of these losses. At a high signal-to-noise ratio (SNR), the precoding loss is dominated by the shaping loss, which is about 1.53 dB. To recover shaping loss, a trellis-shaping technique is developed that takes into account the knowledge of a noncausal interfering sequence, rather than just the instantaneous interference. At rates of 2 and 3 bits per transmission, trellis shaping is shown to be able to recover almost all of the 1.53-dB shaping loss. At a low SNR, the precoding loss is dominated by power and modulo losses, which can be as large as 3-4 dB. To recover these losses, a technique that incorporates partial interference presubtraction (PIP) within convolutional decoding is developed. At rates of 0.5 and 0.25 bits per transmission, PIP is able to recover 1-1.5 dB of the power loss. For intermediate SNR channels, a combination of the two schemes is shown to recover both power and shaping losses.

Realizable lower bounds for time delay estimation. 2. Threshold phenomena

In time delay estimation of narrowband signals the mean square error (MSE) plotted as a function of the signal to noise ratio (SNR) exhibits threshold phenomena. The thresholds divide the domain of SNR values into several disjoint segments. For very low SNR values the observations are dominated by noise and are essentially useless for delay estimation. Here the MSE is determined largely by the available a priori information. For intermediate SNR values, time delay estimates are possible, but are subject to ambiguities resulting from the oscillatory nature of the signal sample correlation. For very high SNR values, these ambiguities are resolvable and the Cramer-Rao bound (CRB) yields a realistic bound for the attainable performance. A previous paper by Zeira and Schultheiss (see IEEE Trans. Signal Processing, vol.41, p.3102-3113, Nov. 1993) used the Barankin (1949) bound to obtain a realizable lower bound for the intermediate SNR region but left open the question where the transitions from low to medium and medium to high SNR operation occur. Since the attainable MSE in the three regions can be very different, the location of the SNR thresholds is of considerable practical interest. The present paper addresses this issue. It obtains threshold values for the single and two echo problems, with emphasis on the effect of echo separation in the two echo case. It concludes that the location of the thresholds is only weakly dependent on echo separation, even though the attainable MSE in both the intermediate and high SNR regions varies drastically as the echo separation changes. >