Let’s face it: real estate is a loud industry. The competition is fierce—and it’s everywhere. But contrary to popular belief, this isn’t a bad thing. With the right strategies in place, you can build a brand that stands out from competitors, earns you more market share and attracts new buyers and sellers in your area.…

The post How to Cut Through Your Competitors’ Noise as a Real Estate Brokerage appeared first on RISMedia.

No matter how good your technical equipment might be, it is almost impossible to avoid capturing unwanted in-/exhaling sounds and mouth noises during voice recordings. After some users asked for an automatic removal of such sounds to improve the audio quality, we got to work and are now proud to present a major upgrade to our Denoiser, including the automatic removal of mouth noises and a new “Remove Breathings” option!
Check out our Audio Examples and the Getting Started Guide below.

What is new?

• Remove Breathings: When the new “Remove Breathings” option is enabled, all the inhalation and exhalation sounds will be muted like all the other noises.
• Eliminate Mouth Noises and Eating Sounds: With our upgrade to the Denoiser, we have integrated the elimination of all types of mouth noises, such as smacking, chewing and clicking. These sounds are set to silence in your output file.

NOTE:
By default, mouth noises and breathing segments are muted but not cut. If you want to cut out all silent segments, just add the “Cut Silence” option for “Automatic Cutting” in the audio algorithms.

Audio Examples

1. Example: Breathing Removal

In our first audio example (Freak Show 136), a speaker breathes directly into the microphone, creating a Darth Vader-like effect. This heavy breathing is removed using the “Remove Breathings” algorithm and the Dynamic Denoiser:

2. Example: Mouth Noise and Eating Sounds Elimination

The following example is an excerpt from the Joe Rogan Experience #2054 where Elon Musk and Joe Rogan are eating pizza and talking about how terrible it is for the sound. Listen to how the chewing and smacking sounds are removed after processing with the new Dynamic Denoiser:

Getting Started Guide

For the Auphonic Web Service:

To remove breathing sounds in the Auphonic Web Service, simply create a production or preset as usual and check the “Remove Breathings” checkbox for “Noise Reduction” in the “Audio Algorithms” section.
“Remove Breathings” is only available for Speech Isolation and the Dynamic Denoiser, but NOT for the Static Denoiser.

For the removal of mouth noises, no special settings are required. Just enable the Speech Isolation or the Dynamic Denoise method for Noise Reduction.

For API Use:

To use “Remove Breathings” with the API, set the "denoisemethod" to dynamic or speech_isolation and the "debreath" flag to true, as in these two examples:

"algorithms": {
    "denoisemethod": dynamic, "denoiseamount": 100, "debreathamount": 100,
}

"algorithms": {
    "denoisemethod": speech_isolation, "denoiseamount": 12, "debreathamount": 100,
}

For more information about the API, please visit our API help page, where you will also find all other API Audio Algorithm Settings.

Conclusion

Breath and mouth noise removal is essential for podcasters, as it enhances audio clarity and ensures a more professional, polished presentation. By removing distracting sounds, you can maintain listener engagement and provide a seamless listening experience.

Anyway, we hope you enjoy the new features!
If you have any feedback for us on how the breath and mouth noise elimination is working for you, please feel free to contact us via email or directly comment in our production interface!

Responding to your feedback, we are now proud to present new separate parameters for noise, reverb, and breath reduction to give you more flexible control for your individual, best output results.
Find all the new parameters below and listen to the Audio Examples to get a closer impression of the upgrade.

What's the update about?

Before

Previously, you could only set the Denoising Method and one reduction amount, that was used for all elements.
Depending on the selected method, you were already able to decide whether music, static, or changing noises should be removed, but there was no setting to keep the typewriter sound effects while removing the reverb, for example.

Now

With our latest upgrade, you can now set the reduction amounts separately for noise, reverb, and breathing sounds.
For example, you could completely remove the background noise while reducing the reverb just a little to enhance speech intelligibility but keep the atmosphere. Like we did in Audio Example 1.
Many of you have also asked about the possibility of slightly reducing breath sounds rather than eliminating them completely. In Audio Example 2 we demonstrate how you can prevent your audio from sounding strange and unnatural by reducing instead of eliminating all breathing sounds.

To all of you who are happy with the results and don't want anything to change, relax:
If you don't change the default settings, the noise reduction algorithms work exactly the same as before.

Note: As the 'Static Denoiser' removes only stationary noise, there are no 'Remove Reverb' and 'Remove Breathings' parameters available for this denoising method.

New Parameters

Screenshot of the new Noise Reduction Parameters in the production form.

In order to use the new noise reduction features, you may separately set the following parameters:

• Denoising Method: (unchanged) Select what kind of noise you want to remove.
  [Dynamic Denoiser (default), Speech Isolation, Static Denoiser]
  Note that the parameters 'Remove Reverb' and 'Remove Breathings' are NOT available for Static Denoiser!
• Remove Noise: Select the amount of noise you want to remove.
  [100 dB (default), Disable Denoise, 3 dB, 6 dB, ..., 100 dB (full)]
• Remove Reverb: Select the amount of reverb you want to remove.
  [100 dB (default), Disable Deverb, 3 dB, 6 dB, ..., 100 dB (full)]
• Remove Breathings: Select the amount of breathings you want to remove.
  [Off (default), 3 dB, 6 dB, ..., 100 dB (full)]

Feel free to experiment with all the options to find your preferred parameter settings! Editing and reprocessing existing productions does not cost any additional credits as long as you don't change the input file.

Listen to the results:

1. Reverb reduction with full noise elimination

For the first audio example by conduitministries.com we set the 'Remove Noise' amount to 100 dB (full) and varied the 'Remove Reverb' amount starting from 0 dB (Off) to 12 dB (medium) and to 100 dB (full). Listen to how first the noise is gone and then step by step the reverb is lower:

2. Breathing sound reduction

In the breathing reduction audio example by LibriVox.org we used the 'Remove Breathing' amounts increasing from the original audio with 0 dB (Off) to 12 dB (medium) and to 100 dB (full) reduction.
In the result files you can hear, that the 100 dB (full) elimination leads to weird, unnatural-sounding pauses, that can be prevented by just reducing the breathing sounds:

Try it now on auphonic.com!

Feedback

We hope you like our upgraded version of the Noise Reduction Algorithms with new parameters for more control.
If you have more feature requests or feedback for us, please let us know! You can also leave a comment in the feedback section on the status page of your specific production. We're looking forward to hearing from you!

Air handlers are the heart of an HVAC system, moving the conditioned air through a building. Like a heart, they can generate a lot of noise while operating. Manufacturers, however, are taking steps to reduce that noise.

Transformers are not perfect. Transients and noise (radio-frequency and low-level spikes) normally pass through transformers, not only by way of the magnetic lines of flux between the primary and the secondary windings but through resistive and capacitive paths between the... Read more

The post The magic that isolation transformer uses to suppress transients and noise appeared first on EEP - Electrical Engineering Portal.

Artificial noise fields under laboratory conditions

Improved impulse noise protection for digital subscriber line (DSL) transceivers

Acoustical smoke vents help reduce exterior noise for new Cincinnati theater.

Technology is improving speech's ability to hear what is necessary.

I’m moving back to http://www.makingthenoise.com Follow me there!

Climate change and insects, and designing Canada’s lunar rover

Great name, better music.

The police say no crime was committed.

Sharon G. Kujawa
Nov 11, 2009; 29:14077-14085
BehavioralSystemsCognitive

Bradley Voytek
Sep 23, 2015; 35:13257-13265
BehavioralSystemsCognitive

Our host, Eric Schulze explains how 1 + 1 = 0 when it comes to sound

An acoustic survey in 2018 and new analysis with A.I. suggest the sounds are vocalizations from the elusive Bryde’s whale

U.K. firm designs smaller scale, more affordable custom test rigs for companies like Rolls Royce to help meet new regulations

Read the in depth Review of Noise Shots XO Audio Video. Know detailed info about Noise Shots XO configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

Read the in depth Review of Noise Shots Rush Audio Video. Know detailed info about Noise Shots Rush configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

Read the in depth Review of Sony WH-1000XM4 Wireless Noise Cancelling headphones Audio Video. Know detailed info about Sony WH-1000XM4 Wireless Noise Cancelling headphones configuration, design and performance quality along with pros & cons, Digit rating, verdict based on user opinions/feedback.

Hi,

I have a question about printing noise summary via maestro output expressions.

How can I print noise data using output expressions, for multiple levels of the hierarchy?

I have found this article which describe the procedure using ocnGenNoiseSummary() function: https://support.cadence.com/apex/ArticleAttachmentPortal?id=a1Od0000007MViHEAW&pageName=ArticleContent

I see also Andrew Beckett referring to the above mentioned article as a solution to a similar question: community.cadence.com/.../noise-summary-per-instance

However, this seems to work only if I'm to extract noise data from a single level of hierarchy.

If I have the output expression "ocnGenNoiseSummary(2 ?result 'hbnoise)", it will generate a "noisesummary" directory under results directory for a hierarchy level of 2.

If I am to extract data from various hierarchy levels, I should be able to generate multiple noise summary directories, such as noisesummary1, noisesummary2 where they correspond to "ocnGenNoiseSummary(1 ?result 'hbnoise)" & "ocnGenNoiseSummary(2 ?result 'hbnoise)", respectively. However this does not seem to be possible.

Can you please advice? Thanks.

My Cadence version: IC23.1-64b.ISR7.27

BR,

Denizhan Karaca

I have tried replicating the setup described in a previous post (here), with the proposed solution.

The MDL measurements return a value of 0 for all exported result but the first.

Using Viva I can actually see the correct value for each contribution.

I am using :
- Spectre 23.1.0.538.isr10
- Viva IC23.1-64b.ISR8.40

What should I do differently?

Thanks!

**** test.measure ****

Measurement Name   :  noi_test
Analysis Type      :  noise
noi_total             =  6.9282e-06
r1_flicker            =  0
r1_thermal            =  0
r1_total              =  0
r2_flicker            =  0
r2_thermal            =  0
r2_total              =  0

The best two headphones deals ahead of Black Friday are the Bose QuietComfort Ultra earbuds on sale for $229 and the Sony WH-1000XM5 headphones for $102.99 off.

Title: Traffic Noise Is (Bad) for the Birds
Category: Health News
Created: 8/28/2018 12:00:00 AM
Last Editorial Review: 8/28/2018 12:00:00 AM

Kelley starts a Reddit fight. Robert learns about purrkour gaming. Pascal makes plans to be a booth babe. Chris eats the mic like it's meat flavored cereal. Mung beans.

The post RPG Cast – Episode 732: “Excited PoE Noises” appeared first on RPGamer.

NASA is investigating a strange noise coming through the speaker on Boeing’s Starliner capsule, which has been beset with technical issues

NASA discovered the cause of a pulsating noise coming from a speaker on the Boeing Starliner spacecraft after astronaut Butch Wilmore reported the sound.

Elemind, a 5-year-old startup based in Cambridge, Mass., today unveiled a US $349 wearable for neuromodulation, the company’s first product. According to cofounder and CEO Meredith Perry, the technology tracks the oscillation of brain waves using electroencephalography (EEG) sensors that detect the electrical activity of the brain and then influence those oscillations using bursts of sound delivered via bone conduction.

Elemind’s first application for this wearable aims to suppress alpha waves to help induce sleep. There are other wearables on the market that monitor brain waves and, through biofeedback, encourage users to actively modify their alpha patterns. Elemind’s headband appears to be the first device to use sound to directly influence the brain waves of a passive user.

In a clinical trial, says Perry [no relation to author], 76 percent of subjects fell asleep more quickly. Those who did see a difference averaged 48 percent less time to progress from awake to asleep. The results were similar to those of comparable trials of pharmaceutical sleep aids, Perry indicated.

“For me,” Perry said, “it cuts through my rumination, quiets my thinking. It’s like noise cancellation for the brain.”

I briefly tested Elemind’s headband in May. I found it comfortable, with a thick cushioned band that sits across the forehead connected to a stretchy elastic loop to keep it in place. In the band are multiple EEG electrodes, a processor, a three-axis accelerometer, a rechargeable lithium-polymer battery, and custom electronics that gather the brain’s electrical signals, estimate their phase, and generate pink noise through a bone-conduction speaker. The whole thing weighs about 60 grams—about as much as a small kiwi fruit.

My test conditions were far from optimal for sleep: early afternoon, a fairly bright conference room, a beanbag chair as bed, and a vent blowing. And my test lasted just 4 minutes. I can say that I didn’t find the little bursts of pink noise (white noise without the higher frequencies) unpleasant. And since I often wear an eye mask, feeling fabric on my face wasn’t disturbing. It wasn’t the time or place to try for sound sleep, but I—and the others in the room—noted that after 2 minutes I was yawning like crazy.

How Elemind tweaks brain waves

What was going on in my brain? Briefly, different brain states are associated with different frequencies of waves. Someone who is relaxed with eyes closed but not asleep produces alpha waves at around 10 hertz. As they drift off to sleep, the alpha waves are supplanted by theta waves, at around 5 Hz. Eventually, the delta waves of deep sleep show up at around 1 Hz.

Ryan Neely, Elemind’s vice president of science and research, explains: “As soon as you put the headband on,” he says, “the EEG system starts running. It uses straightforward signal processing with bandpass filtering to isolate the activity in the 8- to 12-Hz frequency range—the alpha band.”

“Then,” Neely continues, “our algorithm looks at the filtered signal to identify the phase of each oscillation and determines when to generate bursts of pink noise.”

To help a user fall asleep more quickly [top], bursts of pink noise are timed to generate a brain response that is out of phase with alpha waves and so suppresses them. To enhance deep sleep [bottom], the pink noise is timed to generate a brain response that is in phase with delta waves.Source: Elemind

These auditory stimuli, he explains, create ripples in the waves coming from the brain. Elemind’s system tries to align these ripples with a particular phase in the wave. Because there is a gap between the stimulus and the evoked response, Elemind tested its system on 21 people and calculated the average delay, taking that into account when determining when to trigger a sound.

To induce sleep, Elemind’s headband targets the trough in the alpha wave, the point at which the brain is most excitable, Neely says.

“You can think of the alpha rhythm as a gate for communication between different areas of the brain,” he says. “By interfering with that communication, that coordination between different brain areas, you can disrupt patterns, like the ruminations that keep you awake.”

With these alpha waves suppressed, Neely says, the slower oscillations, like the theta waves of light sleep, take over.

Elemind doesn’t plan to stop there. The company plans to add an algorithm that addresses delta waves, the low-frequency 0.5- to 2-Hz waves characteristic of deep sleep. Here, Elemind’s technology will attempt to amplify this pattern with the intent of improving sleep quality.

Is this safe? Yes, Neely says, because auditory stimulation is self-limiting. “Your brain waves have a natural space they can occupy,” he explains, “and this stimulation just moved it within that natural space, unlike deep-brain stimulation, which can move the brain activity outside natural parameters.”

Going beyond sleep to sedation, memory, and mental health

Applications may eventually go beyond inducing and enhancing sleep. Researchers at the University of Washington and McGill University have completed a clinical study to determine if Elemind’s technology can be used to increase the pain threshold of subjects undergoing sedation. The results are being prepared for peer review.

Elemind is also working with a team involving researchers at McGill and the Leuven Brain Institute to determine if the technology can enhance memory consolidation in deep sleep and perhaps have some usefulness for people with mild cognitive impairment and other memory disorders.

Neely would love to see more applications investigated in the future.

“Inverse alpha stimulation [enhancing instead of suppressing the signal] could increase arousal,” he says. “That’s something I’d love to look into. And looking into mental-health treatment would be interesting, because phase coupling between the different brain regions appears to be an important factor in depression and anxiety disorders.”

Perry, who previously founded the wireless power startup UBeam, cofounded Elemind with four university professors with expertise in neuroscience, optogenetics, biomedical engineering, and artificial intelligence. The company has $12 million in funding to date and currently has 13 employees.

Preorders at $349 start today for beta units, and Elemind expects to start general sales later this year. The company will offer customers an optional membership at $7 to $13 monthly that will allow cloud storage of sleep data and access to new apps as they are released.

Elevated medlinkblood pressure/medlink contributes more to cardiovascular disease (CVD) and premature death than any other known and modifiable risk factor.

Loud blasts, such as those from roadside bombs, can cause damaging fluid buildup in inner ear, according to study in mice

Loud blasts, such as those from roadside bombs, can cause damaging fluid buildup in inner ear, according to study in mice

This basic smartwatch tracks a lot of parameters and also lets you easily call contacts from your wrist

The opening night of South Korea’s K-League presented a rare-treat for football fans starved of action, with reigning champions Jeonbuk Motors facing cup champions Suwon Bluewings.

Archives, Room Use Only - TK6169.W47 1934

Explained: How coronavirus lockdown reduced Earth’s seismic noise levels  The Indian Express

UK sees notable reduction in seismic noise caused by human activity – experts  Aberdeen Evening Express

Elucidating the structural dynamics of small molecules and proteins in the liquid solution phase is essential to ensure a fundamental understanding of their reaction mechanisms. In this regard, time-resolved X-ray solution scattering (TRXSS), also known as time-resolved X-ray liquidography (TRXL), has been established as a powerful technique for obtaining the structural information of reaction intermediates and products in the liquid solution phase and is expected to be applied to a wider range of molecules in the future. A TRXL experiment is generally performed at the beamline of a synchrotron or an X-ray free-electron laser (XFEL) to provide intense and short X-ray pulses. Considering the limited opportunities to use these facilities, it is necessary to verify the plausibility of a target experiment prior to the actual experiment. For this purpose, a program has been developed, referred to as S-cube, which is short for a Solution Scattering Simulator. This code allows the routine estimation of the shape and signal-to-noise ratio (SNR) of TRXL data from known experimental parameters. Specifically, S-cube calculates the difference scattering curve and the associated quantum noise on the basis of the molecular structure of the target reactant and product, the target solvent, the energy of the pump laser pulse and the specifications of the beamline to be used. Employing a simplified form for the pair-distribution function required to calculate the solute–solvent cross term greatly increases the calculation speed as compared with a typical TRXL data analysis. Demonstrative applications of S-cube are presented, including the estimation of the expected TRXL data and SNR level for the future LCLS-II HE beamlines.