Tone Detection Research Articles

Passive Tone Detection for Moving Targets Based on Long-Time Coherent Integration

The detection of sinusoidal signals embedded in noise is an important topic in passive sonar signal processing. The performance of existing tone detection techniques is limited by the Doppler frequency shift, which is caused by the relative motion between moving targets and the receiver. In this study, an algorithm based on long-time coherent integration is proposed to achieve robust tonal signal detection under the influence of a Doppler frequency shift. First, the received narrowband signals radiated by moving targets are split into multiple segments through a window-length constraint. The results obtained by applying a discrete Fourier transform (DFT) to the data segments are modeled as a polynomial phase signal in the frequency domain. Then, the polynomial Radon-polynomial Fourier transform (PRPFT) is applied to simultaneously compensate the time-variant frequency drift and phase difference. To avoid the gain loss due to the discretization of the phase difference compensation in PRPFT, a phase compensation factor searching algorithm is proposed. The simulation results show that the proposed algorithm can provide higher frequency resolution and higher coherent integration gain even in the case of a severe Doppler shift. Furthermore, the results of sea trials demonstrate that the proposed method can perfectly achieve coherent integration for signals with a duration of several hundred seconds under different experimental conditions.

Mechanisms of masking by Schroeder-phase harmonic tone complexes in the budgerigar (Melopsittacus undulatus)

Schroeder-phase harmonic tone complexes can have a flat temporal envelope and rising or falling instantaneous-frequency sweeps within F0 periods, depending on the phase-scaling parameter C. Human tone-detection thresholds in a concurrent Schroeder masker are 10-15 dB lower for positive C values (rising frequency sweeps) compared to negative (falling sweeps), potentially due to cochlear mechanics, though this hypothesis remains controversial. Birds provide an interesting model for studies of Schroeder masking because many species produce vocalizations containing frequency sweeps. Prior behavioral studies in birds suggest less behavioral threshold difference between maskers with opposite C values than in humans, but focused on low masker F0s and did not explore neural mechanisms. We performed behavioral Schroeder-masking experiments in budgerigars (Melopsittacus undulatus) using a wide range of masker F0 and C values. Signal frequency was 2800 Hz. Neural recordings from the midbrain characterized encoding of behavioral stimuli in awake animals. Behavioral thresholds increased with increasing masker F0 and showed minimal difference between opposite C values, consistent with prior budgerigar studies. Midbrain recordings showed prominent temporal and rate-based encoding of Schroeder F0, and in many cases, marked asymmetry in Schroeder responses between C polarities. Neural thresholds for Schroeder-masked tone detection were often based on a response decrement compared to the masker alone, consistent with prominent modulation tuning in midbrain neurons, and were generally similar between opposite C values. The results highlight the likely importance of envelope cues in Schroeder masking and show that differences in supra-threshold Schroeder responses do not necessarily result in neural threshold differences.

Prediction and detection of emotional tone in online social media mental disorder groups using regression and recurrent neural networks.

Online social media networks have become a significant platform for persons with mental illnesses to discuss their struggles and obtain emotional and informational assistance in recent years. One such platform is Reddit, where sub-groups called 'subreddits' exist, based on a variety of topics including mental illnesses such as anxiety or depression. We analyse the user's interactions to calculate the mental health status by formulating and using a parameter called 'emotional tone' representing the user's emotional state. VADER sentiment analysis and TextBlob are used to categorise emotional tone and find distribution of emotional polarity and subjectivity of comments. For final tone prediction, RNN and State-Of-The-Art word embedding techniques are used to develop a predictive model. The resultant model provides end-to-end categorization and prediction of emotional tone. We obtain results with respect to Weighted L1 Loss that deals with extreme responses. The MODEL transcends all the baselines by at least 12.1% and the final emotional status of the authors is positive.

TONE DETECTION ON TERANIKA MUSICAL INSTRUMENT USING DISCRETE WAVELET TRANSFORM AND DECISION TREE CLASSIFICATION

Musical instruments are one of the cultures that must be preserved. Teranika is one of the traditional musical instruments from the Majalengka area, which is made of clay. Currently, the manufacture of conventional musical instruments is still done manually, so there are still differences in the tone produced. Meanwhile, the quality of a musical instrument is determined by the accuracy of the technique. Therefore, we need a system that can accurately detect the method's accuracy. The author designed a tone detection system for Teranika musical instruments to help artisans carry out quality control. This system will detect whether or not the musical instrument is successfully matched with the right tone and agent. The technique contained in this musical instrument is Do Re Mi Fa So La Si Do high. To overcome these problems, the author makes this tone detection system using the Discrete Wavelet Transform method and the Decision Tree classification. The working principle of this system is that the recorded sound of musical instruments will be transmitted to this system. Then the sound will be processed as input and matched with the essential voice in the database. The output of this system produces samples according to the sampling frequency used. The test results show the best results at decomposition level 6, a thresholding value of 0.05, and a Fine Tree classification type with an accuracy of 87.5%

Portable automated rapid testing: Validation of automated testing on listeners from India

Portable Automated Rapid Testing (PART) is an iPad application (https://braingamecenter.ucr.edu/games/p-a-r-t/) capable of measuring various psychoacoustic thresholds (speech on speech masking, temporal, spectral, and spectrotemporal modulation detection, temporal gap detection, frequency modulation tasks, and pure tone detection in noise) in an automated and rapid format using commercially available headphones. The app has been validated previously in native speakers of English and an adapted version of the app has been validated in young normal hearing listeners from Mexico. Here, we present psychoacoustic threshold data for a large cohort of younger college going listeners from India whose native language is not English but are proficient in English. The thresholds obtained from this group will be compared against previously published thresholds based on native speakers of English. It is hypothesized that there will not be any significant differences in thresholds between listeners from India and the thresholds published in the literature. These results will give us the required evidence to start using this freely available app to measure reliable thresholds of various central auditory processing measures in non-native speakers of English who are proficient in the language as well.

Fast processing models effects of reflections on binaural unmasking

Sound reflections and late reverberation alter energetic and binaural cues of a target source, thereby affecting its detection in noise. Two experiments investigated detection of harmonic complex tones, centered around 500 Hz, in noise, in a virtual room with different modifications of simulated room impulse responses (RIRs). Stimuli were auralized using the Simulated Open Field Environment’s (SOFE’s) loudspeakers in anechoic space. The target was presented from the front (0°) or 60° azimuth, while an anechoic noise masker was simultaneously presented at 0°. In the first experiment, early reflections were progressively added to the RIR and detection thresholds of the reverberant target were measured. For a frontal sound source, detection thresholds decreased while adding early reflections within the first 45 ms, whereas for a lateral sound source, thresholds remained constant. In the second experiment, early reflections were removed while late reflections were kept along with the direct sound. Results for a target at 0° show that even reflections as late as 150 ms reduce detection thresholds compared to only the direct sound. A binaural model with a sluggishness component following the computation of binaural unmasking in short windows predicts measured and literature results better than when large windows are used.

Machine learning based chroma phase offset detection and correction in motion video

<span lang="EN-US">Generally, chroma phase or hue offset issues within a scene are hard to detect, without a reference or context (i.e. some apriori<em> </em>knowledge about how certain objects within the scene should actually<em> </em>appear in terms of their hue). Moreover, when it comes to skin/flesh tones, hue deviation can be noticeable and can markedly degrade the viewer quality of experience</span><span lang="IN">(QoE)</span><span lang="EN-US">, whenever it does occur. However a lot of research has gone into flesh tone detection, specifically, the color gamut within which flesh tone is present. This topic has been well documented in the literature with respect to various color spaces: red, green, blue (RGB) and YIQ. Therefore, overall issues with chroma offset or hue within the video content could potentially be approached by extracting and analyzing a reliable reference, such as skin or flesh tone (if present), within some allowable deviation. This involves machine learning (ML) based facial recognition and tracking followed by skin tone region recognition within the detected facial sequence (i.e. Region of Interest). The skin region serves as a ‘self-reference’ in order to discern any inherent phase offset within the content. Finally, the angular chroma deviation discerned can then be used for subsequent correction as well.</span><p> </p>

Statistics of the instantaneous interaural parameters for dichotic tones in diotic noise (N0S ψ ).

Stimuli consisting of an interaurally phase-shifted tone in diotic noise-often referred to as N 0 S ψ -are commonly used to study binaural hearing. As a consequence of mixing diotic noise with a dichotic tone, this type of stimulus contains random fluctuations in both interaural phase- and level-difference. We report the joint probability density functions of the two interaural differences as a function of amplitude and interaural phase of the tone. Furthermore, a second joint probability density function for interaural phase differences and the instantaneous cross-power is derived. The closed-form expression can be used in future studies of binaural unmasking first to obtain the interaural statistics and then study more directly the relation between those statistics and binaural tone detection.

Phase Noise Analysis of Resonator-Enhanced Electro-Optic Comb-Based Analog Coherent Receivers

We present an architecture for wavelength-division-multiplexed coherent data center links employing resonator-enhanced electro-optic frequency comb generators as both transmitter and local oscillator (LO) sources. We show that in each frequency comb, the phase noise in all comb lines is determined completely by the optical phase noise of the seed laser and the phase noise of the microwave oscillator. We propose an analog coherent receiver that performs carrier recovery on all wavelength channels using only two phase-locked loops. We use an independent cascade of phase shifters driven by marker tone detection in each channel for polarization recovery and compensation of a static optical phase shift. We study design examples for quadrature phase-shift keying and 16-ary quadrature amplitude modulation (16-QAM), determining requirements on the transmitter and LO seed laser linewidths and the LO frequency modulation (FM) response. We find that for a dual-polarization (DP) 16-QAM link with 17 wavelength channels, each operating at 56 GBaud, if the combined linewidth of the transmitter and LO seed lasers is 100 kHz, the LO seed laser requires an FM response that is flat from d.c. to several hundred MHz to maintain a phase-error penalty below 1 dB.

Decreased Modulation of Population Correlations in Auditory Cortex Is Associated with Decreased Auditory Detection Performance in Old Mice.

Age-related hearing loss (presbycusis) affects one-third of the world's population. One hallmark of presbycusis is difficulty hearing in noisy environments. Presbycusis can be separated into two components: the aging ear and the aging brain. To date, the role of the aging brain in presbycusis is not well understood. Activity in the primary auditory cortex (A1) during a behavioral task is because of a combination of responses representing the acoustic stimuli, attentional gain, and behavioral choice. Disruptions in any of these aspects can lead to decreased auditory processing. To investigate how these distinct components are disrupted in aging, we performed in vivo 2-photon Ca2+ imaging in both male and female mice (Thy1-GCaMP6s × CBA/CaJ mice) that retain peripheral hearing into old age. We imaged A1 neurons of young adult (2-6 months) and old mice (16-24 months) during a tone detection task in broadband noise. While young mice performed well, old mice performed worse at low signal-to-noise ratios. Calcium imaging showed that old animals have increased prestimulus activity, reduced attentional gain, and increased noise correlations. Increased correlations in old animals exist regardless of cell tuning and behavioral outcome, and these correlated networks exist over a much larger portion of cortical space. Neural decoding techniques suggest that this prestimulus activity is predictive of old animals making early responses. Together, our results suggest a model in which old animals have higher and more correlated prestimulus activity and cannot fully suppress this activity, leading to the decreased representation of targets among distracting stimuli.SIGNIFICANCE STATEMENT Aging inhibits the ability to hear clearly in noisy environments. We show that the aging auditory cortex is unable to fully suppress its responses to background noise. During an auditory behavior, fewer neurons were suppressed in the old relative to young animals, which leads to higher prestimulus activity and more false alarms. We show that this excess activity additionally leads to increased correlations between neurons, reducing the amount of relevant stimulus information in the auditory cortex. Future work identifying the lost circuits that are responsible for proper background suppression could provide new targets for therapeutic strategies to preserve auditory processing ability into old age.

Tone in Noise Detection in Children with a History of Temporary Conductive Hearing Loss.

Children with a history of temporary conductive hearing loss (CHL) during early development may show long-term impairments in auditory processes that persist after restoration of normal audiometric hearing thresholds. Tones in noise provide a simplified paradigm for studying hearing in noise. Prior research has shown that adults with sensorineural hearing loss may alter their listening strategy to use single-channel energy cues for tone-in-noise (TIN) detection rather than rove-resistant envelope or spectral profile cues. Our objective was to determine the effect of early CHL on TIN detection in healthy children compared to controls. Children ages 4-7years, with and without a history of CHL due to otitis media with effusion (OME) before age 3years, participated in a two-alternative forced choice TIN detection task. Audiometric thresholds were normal at the time of testing. Thresholds for detection of a 1000Hz tone were measured in fixed-level noise and in roving-level noise that made single-channel energy cues unreliable. Participants included 23 controls and 23 with a history of OME-related CHL. TIN thresholds decreased with increasing age across participants. Children in both groups showed similar TIN sensitivity and little or no threshold elevation in the roving-level condition compared to fixed-level tracks, consistent with use of rove-resistant cues. In contrast to older listeners with sensorineural hearing loss, there was no detectable change in TIN sensitivity with roving level for children with a history of OME-related CHL.

A High Performance Dual Stage Face Detection Algorithm Implementation using FPGA Chip and DSP Processor

A dual stage system architecture for face detection based on skin tone detection and Viola and Jones face detection structure is presented in this paper. The proposed architecture able to track down human faces in the image with high accuracy within time constrain. A non-linear transformation technique is introduced in the first stage to reduce the false alarms in second stage. Moreover, in the second stage pipe line technique is used to improve overall throughput of the system. The proposed system design is based on Xil¬inx’s Virtex FPGA chip and Texas Instruments DSP processor. The dual port BRAM memory in FPGA chip and EMIF (External Memory Interface) of DSP processor are used as interface between FPGA and DSP processor. The proposed system exploits advantages of both the computational elements (FPGA and DSP) and the system level pipelining to achieve real time perform¬ance. The present system implementation focuses on high accurate and high speed face detec¬tion and this system evaluated using standard BAO image database, which include images with different poses, orientations, occlusions and illumination. The proposed system attained 16.53 FPS frame rate for the input image spatial resolution of 640X480, which is 23.4 times faster detection of faces compared to MATLAB implementation and 12.14 times faster than DSP implementation and 2.1 times faster than FPGA implementation.

Underwater Tone Detection with Robust Coherently-Averaged Power Processor

The detection of tonal signals with unknown frequencies is an important area of study in underwater signal processing. A common approach to address this issue is to use the Discrete Fourier Transform (DFT) for observations. When a tone does not lie precisely at the discrete DFT frequency point, its energy will leak to adjacent frequency point. This phenomenon is known as scalloping loss or Picket Fence Effect (PFE). PFE leads to the degradation of detection performance based on DFT. This paper studies the problem of robust detection in the case of PFE. A coherently-averaged power processor utilizing the information of adjacent frequency bins is designed. The results of simulations and experiments show that the proposed method is robust against PFE, and is highly suitable for tone detection in practical circumstances.

Effects of attentional focus and cognitive load on novice dart throwing: Evidence from quiet eye duration and pupillary responses

The purpose of the present study was to investigate the effects of attentional focus and cognitive-load on motor performance, quiet-eye-duration, and pupil dilation. 18 participants completed a dart throwing task under four conditions, internal or external focus with high or low cognitive-load. Cognitive-load was created by a secondary tone detection task. During each trial participants pupil size and eye movements were recorded along with accuracy data of the dart throw. Results revealed that decreased cognitive-load increased accuracy while high load increased pupil size (p's < 0.05). An external focus resulted in the greatest accuracy while an external focus with high cognitive-load resulted in the longest quiet-eye-durations (p's < 0.05). Based on these findings an increase in pupil size is related to greater cognitive-load but doesn't explain the improvement in task performance. Likewise, an external focus of attention improved performance but was not strongly related to quiet-eye-duration. Results are further discussed in the article.

Merging the Psychophysical Function With Response Times for Auditory Detection of One vs. Two Tones.

The purpose of this study is to take preliminary steps to unify psychoacoustic techniques with reaction-time methodologies to address the perceptual mechanisms responsible for the detection of one vs. multiple sounds. We measured auditory redundancy gains for auditory detection of pure tones widely spaced in frequency using the tools of Systems Factorial Technology to evince the system architecture and workload capacity in two different scenarios (SOFT and LOUD). We adopted an experimental design in which the presence or absence of a target at each of two frequencies was combined factorially with two stimulus levels. Replicating previous work, results did not allow an assessment of system architecture due to a failure to observe factor influence at the level of distribution ordering for dual-target stimuli for both SOFT and LOUD scenarios. All subjects demonstrated very modest redundancy gains for the dual-target compared to the single-target stimuli, and results were similar for both LOUD and SOFT. We propose that these results can be predicted by a mental architecture that falls into the class of integrated subadditive parallel systems, using a well-supported assumption that reaction time is driven by loudness. We demonstrate that modeled loudness of the experimental sounds (which ranged between about 0.2 and 14 sones) is highly correlated with mean reaction time (r = −0.87), and we provide a proof-of-concept model based on Steven’s Power law that predicts both a failure of distributional ordering for dual-target stimuli and very modest redundancy gains.

Rate Discrimination Training May Partially Restore Temporal Processing Abilities from Age-Related Deficits.

The ability to understand speech in complex environments depends on the brain’s ability to preserve the precise timing characteristics of the speech signal. Age-related declines in temporal processing may contribute to the older adult’s experience of communication difficulty in challenging listening conditions. This study’s purpose was to evaluate the effects of rate discrimination training on auditory temporal processing. A double-blind, randomized control design assigned 77 young normal-hearing, older normal-hearing, and older hearing-impaired listeners to one of two treatment groups: experimental (rate discrimination for 100- and 300-Hz pulse trains) and active control (tone detection in noise). All listeners were evaluated during pre- and post-training sessions using perceptual rate discrimination of 100-, 200-, 300-, and 400-Hz band-limited pulse trains and auditory steady-state responses (ASSRs) to the same stimuli. Training generalization was evaluated using several temporal processing measures and sentence recognition tests that included time-compressed and reverberant speech stimuli. Results demonstrated a session × training group interaction for perceptual and ASSR testing to the trained frequencies (100 and 300 Hz), driven by greater improvements in the training group than in the active control group. Further, post-test rate discrimination of the older listeners reached levels that were equivalent to those of the younger listeners at pre-test. Generalization was observed in significant improvement in rate discrimination of untrained frequencies (200 and 400 Hz) and in correlations between performance changes in rate discrimination and sentence recognition of reverberant speech. Further, non-auditory inhibition/attention performance predicted training-related improvement in rate discrimination. Overall, the results demonstrate the potential for auditory training to partially restore temporal processing in older listeners and highlight the role of cognitive function in these gains.

Busy and confused? High risk of missed alerts in the cockpit: An electrophysiological study

The ability to react to unexpected auditory stimuli is critical in complex settings such as aircraft cockpits or air traffic control towers, characterized by high mental load and highly complex auditory environments (i.e., many different auditory alerts). Evidence shows that both factors can negatively impact auditory attention and prevent appropriate reactions. In the present study, 60 participants performed a simulated aviation task varying in terms of mental load (no, low, high) concurrently to a tone detection paradigm in which the complexity of the auditory environment (i.e., auditory load) was manipulated (1, 2 or 3 different tones). We measured both detection performance (miss, false alarm, d’) and brain activity (event-related potentials) associated with the target tone. Our results showed that both mental and auditory loads affected target tone detection performance. Importantly, their combined effects had a large impact on the percentage of missed target tones. While, in the no mental load condition, miss rate was very low with 1 (0.53%) and 2 tones (1.11%), it increased drastically with 3 tones (24.44%), and this effect was accentuated as mental load increased, yielding to the higher miss rate in the 3-tone paradigm under high mental load conditions (68.64%). Increased mental and auditory loads and miss rates were associated with disrupted brain responses to the target tone, as shown by a reduced P3b amplitude. In sum, our results highlight the importance of balancing mental and auditory loads to maintain efficient reactions to alarms in complex working environment.

Computer-based musical interval training program for Cochlear implant users and listeners with no known hearing loss.

A musical interval is the difference in pitch between two sounds. The way that musical intervals are used in melodies relative to the tonal center of a key can strongly affect the emotion conveyed by the melody. The present study examines musical interval identification in people with no known hearing loss and in cochlear implant users. Pitch resolution varies widely among cochlear implant users with average resolution an order of magnitude worse than in normal hearing. The present study considers the effect of training on musical interval identification and tests for correlations between low-level psychophysics and higher-level musical abilities. The overarching hypothesis is that cochlear implant users are limited in their ability to identify musical intervals both by low-level access to frequency cues for pitch as well as higher-level mapping of the novel encoding of pitch that implants provide. Participants completed a 2-week, online interval identification training. The benchmark tests considered before and after interval identification training were pure tone detection thresholds, pure tone frequency discrimination, fundamental frequency discrimination, tonal and rhythm comparisons, and interval identification. The results indicate strong correlations between measures of pitch resolution with interval identification; however, only a small effect of training on interval identification was observed for the cochlear implant users. Discussion focuses on improving access to pitch cues for cochlear implant users and on improving auditory training for musical intervals.

Human Skin Tone Detection

Human skin tone variation can be easily seen from person to person within the same ethnic group or different ethnic group. The skin tone is analysed by melanosome size, significant and progressive variation in size and ethnicity. In face recognition the shape of the face gets identified but background used in real time is usually complex with varying lighting conditions. Automatic skin detection has been intensively studied for human-related recognition systems. The Gaussian model for skin detection is with its generality but they lack in their accuracy. Hence we suggest a new statistical colour model for skin detection called an elliptical boundary model. Detection and tracking of human face and hands are used for gesture recognition and to handle the domain transfer problem. The elliptical boundary model overcomes the limitations of the Gaussian model with better performance based on six chrominance spaces on the face, giving a much higher correct detection ratio with faster speed. For that, we are processing with two main domains that are Full stack development which handles the frontend and backend of the application and Machine Learning algorithms which handles the detection of the skin tone. Here we are dealing with image processing techniques for input and the output will find the skin tone of that particular image that we are processing. The applications that involve skin tone detection are face detection, gesture recognition and image filtering. Hence they overcome the different illumination conditions as different domains of skin pixels. The objective of the project is to detect the skin tone from a human face image with various tone characteristics. We are detecting the basic tone differentiation (Fair, Mild or Dark).

Implementation of Computer-Aided Piano Music Automatic Notation Algorithm in Psychological Detoxification.

This paper analyzes the modeling of a computer-aided piano music automatic notation algorithm, combines the influence of music on psychological detachment, and designs the piano music automatic notation algorithm in psychological detachment model construction. This paper investigates the multiresolution time-frequency representation constant Q-transform (CQT), which is common in music signal analysis, and finds that although CQT has higher frequency resolution at low frequencies, it also leads to lower temporal resolution. The variable Q-transform is introduced as a tool for multibasic frequency estimation of the time-frequency representation of music signals, which has better temporal resolution than CQT at the exact frequency resolution and efficient coefficient calculation. The short-time Fourier transform and constant Q-transform time-frequency analysis methods are implemented, respectively, and note onset detection and multibasic tone detection are implemented based on CNN models. The network structure, training method, and postprocessing method of CNN are optimized. This paper proposes a temporal structure model for maintaining music coherence to avoid manual input and ensure interdependence between tracks in music generation. This paper also investigates and implements a method for generating discrete music events based on multiple channels, including a multitrack correlation model and a discretization process. In this paper, the automatic piano music notation algorithm can play an influential role in significantly enhancing the actual effect of psychological detoxification.