Category: Audio Forensics

Audio ForensicsComputer ForensicsCrisis ManagementOnline Reputation ManagementSocial Media

Deepfake: Its Role in Law, Perception, and Crisis Management (Part 2)

Welcome to Part 2 of Experts.com’s Deepfake Blog Series! In case you missed it, check out Part 1. The focus for Part 2 is to delve into the legal ramifications and perceptive dangers of deepfake videos, along with solutions for individuals and organizations who have been negatively affected by deceptive content. Continued insight from Audio, Video, and Photo Clarification and Tampering Expert, Bryan Neumeister, and new knowledge from fellow Experts.com Member and Online Reputation Management Expert, Shannon Wilkinson, will be included in this post.

Due to the relatively new concept and technology of deepfake content, the legal ramifications are not concrete. In fact, admitting deepfake content as evidence in some criminal and civil court cases can be a precarious endeavor because of metadata. According to the Oxford Dictionary, metadata is “information that describes other information.” Think of metadata as information found on a book. Listed is the author’s name, summary of the author, synopsis of the book, the name and location of the publishing company, etc. Metadata answers the same inquiries about videos and photographs on the internet. It has even been used to solve crimes. For example, in 2012, law enforcement found John McAfee, a man who ran from criminal prosecution for the alleged murder of his neighbor, using the metadata from a photo VICE Media, LLC released in an interview with the suspect (NPR). “The problem with metadata is when you upload any video to YouTube or Facebook, the metadata is washed because the user gives up the right to the video,” a statement by Bryan Neumeister. Reasons vary as to why metadata is removed. Some platforms have policies to disregard metadata to expedite the download time for such images and videos. However, it raises concern for those interested in preserving intellectual property (Network World). In addition to the numerous reposts a photo or video acquires, finding the original author of a post on major social media platforms poses a problem for litigants.

Entering evidence into court becomes a Chain of Custody issue (702, 902) through the Daubert Standard, which is a set of criteria used to determine the admissibility of expert witness testimony. Part of Mr. Neumeister’s expertise is to sift through the components (time stamp, camera, exposure, type of lens, etc.) of digital evidence via computer software systems to determine its authenticity or modification. One of the many techniques he uses is to look at the hash value of digital evidence. According to Mr. Neumeister, “Hash values are referred to in Daubert 702 as a way to authenticate. Think about a hash value as a digital fingerprint.” Without this set of numerical data, the most vital piece of proof needed to discern an original from a fake photograph or video, the digital evidence should be ruled as inadmissible by Daubert standards, as there is no chain of custody to a foundational original. Because deepfakes are difficult to track, and perpetrators are mainly anonymous underground individuals with limited assets, prosecuting these cases is a long-term investment without the return. From a moral perspective, justice should be served. With little or no recourse, the frustration is overwhelming for people whose character and financial future have been put in jeopardy.

Deepfakes may be complicated in the legal arena, but in the world of public perception, its role is much more forthright. In recent years, perception has become reality, and this notion rings resoundingly true regarding deepfake content. People who create and publish deceitful content have three main goals: to tarnish a person or company’s reputation, change a narrative, and ultimately influence the public. “Deepfakes are not usually done by big corporations. There is too much at stake. They are usually done by groups that have an intent to cause misdirection,” a direct quote by Mr. Neumeister. The truth about events regarding politicians, or any other public figure, has now become subjective. Like most viral posts, once a deepfake video is released, unless a user participates in research and finds other sources that confirms or denies deceptive material, people will believe what is shown on social media. There are two reasons for this: 1) it confirms an already ingrained bias, and 2) some people would rather trust the information instead of actively looking for sources that contradict the deepfake due to lack of will or information overload. Studies have shown it takes just a few seconds to convince people who are leaning the way a deepfake video is portraying a situation to believe the content. Even if there is a source that has been fact-checked and proves the contrary, the damage to a public figure’s perception has already been done.

For instance, one of the most popular types of deepfakes are centered around pornography. As discussed in Part 1, the General Adversarial Network (GANs) generated deepfake videos have a specific algorithmic structure that accumulates multitudes of any footage and mimics the desired output data. However, its blatantly realistic and high-quality footage is too exaggerated to be an authentic video. To further augment the illusion, people use techniques such as adding background noise, changing the frame rate, and editing footage out of context to make the video more “realistic.” According to Mr. Neumeister, “The more you dirty it up, the harder it is to tell … and then you’ve got enough to make something convincing that a lot of people won’t fact check.” This unfortunate reality, the emergence of different types of deepfake content can ruin the reputations of individuals and businesses across the board. Fortunately, there are methods to managing public perception.

A positive public image is one of the driving forces for success, trust, revenue, and a growing client base. For this reason, malicious and manipulative material found on the internet is threatening. The internet allows everyone to become an author, which gives users the power to post a variety of content ranging from true stories to false narratives. When businesses and organizations find themselves in a fraudulent crisis, “it can impact shareholder value, damage an organization’s reputation and credibility in the eye of consumers and customers, and result in the dismissal or stepping down of a CEO, board members, and/or other key leaders,” stated by Shannon Wilkinson, an Online Reputation Management Expert. Individuals who have less of a digital presence than organizations are more at risk for facing defamatory content. It begs the question, what types of crisis management strategies can business and individuals use to defend themselves against deepfake content?

One of the reasons why crisis emerges for organizations and public figures is due to the lack of proactiveness. Luckily, Ms. Wilkinson has provided numerous tips on how to prioritize reputation management and crisis response to build a “powerful digital firewall.” For reputation management, Ms. Wilkinson recommends:

  • Understanding how one’s business and brand appears to the world.
    • “Each Google page has 10 entries, discounting ads…The fewer you ‘own’ – meaning ones you publish… – the less control you have over your online image,” according to Ms. Wilkinson.
  • Customizing LinkedIn and Twitter profiles.
  • Publishing substantive and high-quality content related to one’s field of expertise or organizations (white papers, blogs, articles, etc.).
  • Scheduling a professional photography session.
  • Creating a personal branding website (ex: http://www.yourname.com).

As for crisis response options, there are two key components businesses and individuals must consider before crafting a recovery plan:

  • Possessing an online monitoring system alerting when one’s brand is trending on social media (ex: Google Alerts and Meltwater)
  • Seeing conversations in real time to augment one’s social presence within those digital spaces.

Below are the recommendations regarding the actual response to a crisis:

  • Social media platforms like Facebook and Twitter seem to be the more popular spaces to respond to deepfake content.
  • Updating current and existing information is a vital strategy to counter attacks.
  • Avoid engaging with anonymous commentors and trolls.
  • “Video is an excellent tool for responding to situations that result in televised content. A well-crafted video response posted on YouTube will often be included in that coverage. This strategy is often used by major companies,” a direct quote from Ms. Wilkinson.

The why behind creating, manipulating, and posting deepfakes for the world to see seems to be a moral dilemma. The motives behind uploading such misleading content are different for those who participate but nefarious, nonetheless. Legally, it remains an area of law where justice is not always served. Thanks to our Experts.com Members, Bryan Neumeister and Shannon Wilkinson, the what, when, how, and where aspects of deepfake content have been explained by people who are well-versed in their respective fields. In the height of modern technology and the rampant spread of misinformation, our Experts advise all online users, entrepreneurs, public figures, and anyone with access to the internet adequately fact-check sources encountered on the web. Those associated with businesses or happen to be public figures should prioritize developing crisis management precautions. In Mr. Neumeister’s own words, “People can destroy a city with a bomb, but they can take down a country with a computer.”

Audio ForensicsComputer ForensicsExpert WitnessSocial Media

Deepfake: An Introduction (Part 1)

Computer technology is one of the most pivotal inventions in modern history. Artificial Intelligence, smartphones, social media, and all related apparatus have significantly enhanced living conditions in an unprecedented manner and connected the world with a click of a button. It is used in various occupations: from business related fields to more creative professions. To say modern technology has been advantageous in recent decades is an understatement. However, every creation has its flaws. This multi-part blog series is intended to reveal one of those flaws, and a dangerous one at that, deepfake videos. This first post includes an introduction to deepfake videos, and the steps taken by federal and state governments to identify such duplicitous content. Special insight on the subject is provided by our Experts.com Member and Audio, Video, and Photo Clarification and Tampering Expert, Bryan Neumeister.

Editing footage and photos is normal practice in our selfie-addicted new normal, but creating distorted content is a whole new ballgame. According to CNBC, deepfakes are “falsified videos made by means of deep learning.” These videos, images, audios, or other digital forms of content are manipulated such that counterfeits pass as the real thing. What makes matters worse is the internet allows anyone and everyone to create, edit, and post deceptive content. It is one of many threats to cybersecurity strategists, police departments, politicians, and industries alike because the purpose of making them is to spread misinformation, tarnish reputation’s, exploit evidence, and to ultimately deceive an audience. The unfortunate reality is deepfake videos which display pornographic scenarios and manipulated political moment are the most common. For instance, a notable deepfake video was posted by Buzzfeed in 2018 depicting former United States president, Barack Obama, slandering another former United States president, Donald Trump. However, the voice behind Obama is none other than Jordan Peele. The video was intended as a moral lesson to explain how important it is to verify online sources, and to highlight the dangerous problem of trusting every post uploaded to the internet.

According to Mr. Neumeister, who specializes in this area of expertise, there are two types of artificial intelligence programs used to create deepfake videos: GANs and FUDs. He states, “GANs (Generative Adversarial Networks) are used by professionals, and FUDs (Fear, Uncertainty, and Doubt) are the homemade ones.” Although FUD videos garner more attention among internet users, the real menace to society are the videos made from GANs.

Videos made from Generative Adversarial Networks have an algorithmic framework designed to acquire input data and mimic the desired output data. One can visualize how GANs work through the viral Tom Cruise TikTok deepfake. According to NPR, the creator of the deepfake, Chris Ume, used a machine-learning algorithm to insert an accumulation of Tom Cruise footage. This allowed him to give a digital face transplant to the Tom Cruise lookalike actor he hired for the video. Ume input a plethora of videos to create a desired output of a realistic face swap. Neumeister also adds that the most realistic deepfakes correlate to the amount of footage a person can acquire. Specifically, “the more bits of video clip you have to put together, the more accurate you can make facial movements, ticks, etc.” From this logic, it can be inferred that Ume’s Tom Cruise deepfake looks more realistic than those that lack algorithmic programs.

Because viewers typically see deepfakes in politics and pornography, federal and state governments have recently implemented laws to counteract deepfake content creation and distribution. President Trump signed the first deepfake federal law near the end of 2019. This legislation is included in the National Defense Authorization Act for Fiscal Year 2020 (NDAA), which is a $738 billion defense policy bill passed by both Senate (86-8) and the House (377-48). The two provisions in the NDAA requires:
“(1) a comprehensive report on the foreign weaponization of deepfakes; (2) requires the government to notify Congress of foreign deepfake-disinformation activities targeting US elections,” (JD Supra). The NDAA also implemented a “Deepfakes Prize” competition to promote the investigation of deepfake-detection technologies. On a state level, there have been laws passed by multiple states that criminalize specific deepfake videos (JD Supra):

  • Virginia: first state to establish criminal penalties on the spread of nonconsensual deepfake pornography.
  • Texas: first state to ban creation and dissemination of deepfake videos aimed to alter elections or harm candidates for public office.
  • California: victims of nonconsensual deepfake pornography can sue for damages; candidates for public office can sue organizations and individuals that maliciously spread election-related deepfakes without warning labels near Election Day.

Although the Trump administration and various states established policies against deepfakes, it remains ubiquitous on almost all online platforms. How can users at home distinguish authentic content from deepfakes?

Mr. Neumeister provides a few tips and tricks for detecting a deepfake. One giveaway mentioned is mouth movement, otherwise known as phonemes and visemes. Mouths move a certain way when people speak. For instance, words like mama, baba, and papa start with a closed mouth. Words like father, and violin start with the front teeth pushing against the bottom lip. To add, consonants and vowels also sound a certain way when pronounced correctly. “Words with t, f, n, o, and wh, are pretty good for tells,” adds Mr. Neumeister. When analyzing video, the frames in which a person is speaking are broken down into approximately six to ten frames to determine if the way someone talks in other videos is the same as the video being analyzed. Another tip Mr. Neumeister suggests is to watch videos with context in mind. Viewers should pay attention to background noise, crowd ambiance, and the cadence in a speaker’s sentences. Authentic and original content would have, by nature, realistic frames. Users can detect a deepfake by sensing dissonance in, for instance, a speaker’s proximity to the microphone or a size of a room. For users at home or on-the-go, these tips are crucial for distinguishing verified sources from manipulated misinformation.

The emergence of deepfake content, its continuously improving technology, and the spread of disinformation is a multifaceted and complex problem. This blog post has only scratched the surface, so stay tuned for part 2 for a more in-depth read.

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Laurel v. Yanny: An Audio Forensics Expert Witness Scientifically Settles the Dispute

On Tuesday of this week, the Internet erupted in a dispute over an audio recording of a word. Or, maybe two words. Nobody knows because nobody can agree. I know what you’re thinking, “We’re so glad Nick decided to write about a viral Internet sensation that we’re already tired of hearing about.” I feel your sarcasm and I reject it. The confusion over the word got me thinking we may be unable to trust our ears. If we cannot trust our hearing, what impact might that have on recorded evidence presented at trial? Or, in a less formal matter (disagreements with a loved one)?

CLICK HEAR FOR THE RECORDING

The New York Times did a good job of addressing the Laurel v. Yanny dispute in this article. They created a tool that allowed readers to change the frequency of the audio recording. Move the arrow all the way to the left and your clearly hear the word “Laurel.” Move it all the way to the right and you hear “Yanny.” Regardless of where the arrow was stationed, disagreement exists.

Don’t worry, I did some research for this article. Using a non-scientific methodology, which is definitely NOT generally accepted in the audio forensics community, I came to some totally unreliable conclusions. Asking friends, family, and coworkers what they heard on the recording, I came to some interesting conclusions. More women heard Yanny and more men heard Laurel. I’m certain the margin of error is enormous and I can’t recall if I asked an even number of men and women. It also appears to be some different interpretations based on age. Then of course, some people heard different words, at different times, on different devices. This really caused problems for my non-scientific research. I heard Laurel one day on one device and Yanny another day on another device.

Naturally, all of this made me wonder how we can trust our hearing? How is evidence reliable? What about witness testimony about what was heard? Of course, I also wondered if science could settle the dispute?

Is testimony about what was heard as unreliable as eyewitness identification testimony?

Eyewitness identification used to be considered incredibly strong evidence. In fact, in some US jurisdictions, it is still compelling evidence. From my experience working with expert witnesses and following the science with some interest for the last eight years, I can tell you that eyewitness identification evidence is terribly unreliable. It is frightening how often it is wrong. There are so many variables which can impact the judgement, perceptions, and memories of an eyewitness, that I would not trust it (without some strong corroborating evidence).

So, I wonder if the hearing of an eyewitness is similarly compromised? How do I know if a witness heard three or five gun shots? How do we know the witness heard one collision or two? What about business negotiations? Are we certain we’re all hearing the same thing and agreeing to the same terms being memorialized in the contract?

Typically, I am more inclined to believe recorded evidence because I am biased against eyewitness testimony from the scientific studies I’ve read. Or, should I say, I was more inclined to believe recorded evidence.

After the Laurel/Yanny dispute, I wondered if recorded audio evidence is reliable? If I can hear one thing and others hear something totally different, how can we rely on a recording? For insights on this phenomena, I’ve reached out to an audio forensics expert.

Herbert Joe – Forensic Audio Video Analysis Expert Witness

Herbert Joe is a highly qualified and board certified forensic audio and video examiner. He has three science degrees and two law degrees. He and his partner have been retained in thousands of criminal, civil, and administrative cases throughout the US and internationally. Mr. Joe has worked on many high-profile matters including the Branch Davidian case, State of Florida vs. George Zimmerman; the Associated Press (Osama bin Laden); consultations with Dr. Phil (Manti Teo), CSI: Miami, TMZ (Michael Jackson), the Wall Street Journal, and People Magazine (Mel Gibson). You can learn more about Mr. Joe by visiting his website: forensicscenter.com.

As I normally do for blogs, I posed several questions to Mr. Joe. Please see my questions and his answers below:

Nick: Some listeners hear Laurel and others hear Yanny. Is this a result of the recording or the listener’s hearing?

Mr. Joe: What one hears has a large subjective component, and even then the same listener may hear it differently over time, depending on a host dynamic factors. For examples, what one perceives to hear may depend largely on the mood or emotive state of that person at that time; what one perceives to hear may depend largely on what s/he is expecting or anticipating to hear; what one perceives to hear may depend largely on one’s hearing ability. Clearly, there are many other factors to determine and affect what one hears, what one interprets and what one recalls, all of which may change over time for that person, and may be very different from what another person perceives to hear.

This only scratches the surface of the area of psychoacoustics, speech production and speech perception.

Nick: Is there a correct answer to Laurel or Yanny?

Mr. Joe: Hate to sound like an attorney – as I am one – but the answer to that question depends, depends on how you phrase that question. Is there a correct answer to what one hears? Yes, it’s what one perceives. But if one clearly enunciates either name/word, then there is an objectively correct answer, namely (sorry for the pun), the word that was spoken or played back – regardless of how it was heard, if at all, by the listener(s).

Consider this analogy with light. We know that our eyes are sensitive to light within the (narrow) visible light spectrum, a small part of the entire electromagnetic spectrum. So let’s take a red apple. Sunlight or white light is made up of all the different color lights that we know of, as we learned in school – ROY G BIZ, red, orange, yellow, blue, green, indigo and violet. But that apple is red, whether we perceive it that way or not. It’s red because the skin of that apple absorbs all the colors of the incoming white light except red, which is reflected and that’s why we see red. (If we shine a pure red light on that apple and no other light is present in a closed room, then that apple will not appear because all the red light is absorbed, and since there is no other light frequency to reflect, then there is no light to perceive, i.e., it appears black.

Likewise, sound is merely vibrations of air that propagates from the source (through the air or another medium) and can be heard when they reach a person’s or animal’s ear. That’s the objective part – the frequencies at whatever intensities at any given moment. It’s there whether we can appreciate them or not.

Nick: Is there a way to determine the correct answer?

Mr. Joe: There is a correct answer if the question is whether there are linguistic and acoustic differences between the spoken words “Laurel” or “Yanny.” See answer to question #5, below.

Nick: If listeners are hearing different words, how can recorded evidence be trusted?

Mr. Joe: For the past 31 years, my partner and I have been forensically analyzing audio, acoustic, voice and video evidence in state and Federal courts, in civil, criminal and administrative cases throughout the U.S., as well as many foreign countries. Recorded evidence must be subjected to admissibility standards to be admitted, and the subject to analyses and opinions that go to the weight of the evidence. If the proponent of the audio (or acoustic, voice or video) evidence can provide facts sufficient to support a reasonable jury determination that the recording is an accurate reproduction of the event that it purports to record. Where we often get retained is to show and testify, objectively and with a reasonable degree of scientific certainty, that the recording has been falsified or tampered with in one way or another to render the recording untrustworthy as a whole. Now if the case comes down to an interpretation or dispute of what was said in some recording, we can enhance (digital signal processing) the passage(s) of interest, allow the jurors to hear the enhanced audio (with good quality headphones), provide a reasonably accurate transcript and provide expert testimony thereof. However, the other side can also have their transcript version of the recording, and it is up to the jury to ultimately decide what the recorded evidence says or not say.

Nick: If the Laurel/Yanny recording was presented as evidence at trial, what analysis would you use to prove one word or the other?

Mr. Joe: We had a case in which the entire felony indictment centered on a single, mono-syllabic word. The Government contended that the Defendant said “Shoot the [expletive]!” The Defendant claimed that he said “Shoot me, [expletive]!” The Government contended the former exclamation underscored intent and contentment that an officer was killed. The defense contended that the latter showed his remorse. So, we had to objectively differentiate between the /th/ sound and the /m/ sound with a reasonable degree of scientific certainty – regardless of what perceives to hear. The /th/ sound is known as a fricative because the tip of the tongue is placed just behind the two front (central) incisors to create friction in producing the /th/ sound. The /m/ sound is known as a nasal sound since air bypasses the oral cavity because the lips are closed (and the soft palate drops) and thus passes out through the nasal passages. After enhancing the audio evidence, spectral analyses revealed the 2nd word had higher frequency energy (“the”, as opposed to lower frequency energy, which would indicate the nasal sound /m/); so, that 2nd word was “me” and not “the.” The case was dismissed upon our testimony.

Likewise, phonetically, Laurel begins with the letter “L,” whereas Yanny begins with the letter “Y.” Although the letter “Y” (a/k/a a semivowel) can represent a vowel or a consonant, it is used as a consonant in “Yanny.” Therefore, on the one hand, there are common phonetic features of the consonants “L” and “Y,” e.g., they are both voiced consonants produced by directing air solely with the lungs and diaphragm and actively narrowing the vocal tract upon articulation. In making either of these sounds, air only leaves through the mouth. On the other hand, there is a substantial phonetic difference between these 2 letters. The letter “L” is a “lateral” consonant, as it is made by directing the airstream around the sides of the tongue upon articulation; the letter “Y” is a “central” consonant, because it is made by directing the airstream along the center of the tongue upon articulation.

One can “see” this substantial difference in the raw waveform, as well as the same waveform viewed as a 3-dimensional spectrogram. Below is the waveform of my enunciating “Laurel,” and then “Yanny.” Below that is a spectrogram of the exact same recording. And one certainly should be able to hear and perceive the difference if the sound source is accurate in the enunciation of each.

laurel-yanny-graph-1.PNG

laurel-yanny-graph-2.PNG

Nick: The Laurel/Yanny recording is of a robotic voice. Are human voices less susceptible to this type of misinterpretation?

Mr. Joe: First, I’m not sure if I agree with the premise. Human voices naturally have varying degrees of emotions manifested by simultaneous changes in pitch, resonance, fluency, intonation, prosody and duration of the words and speech segments. In contrast, computer-generated, synthetic or robotic speech utilizes an algorithm that translates orthographic strings of letters into the robotic voice; however, synthetic voice is audibly missing emotive components, like the natural variations in pitch, level, and intonation.

But it’s not so much misinterpretation, as it is how the brain perceives the difference: human speech requires little effort by our auditory cortex when perceived; however, synthetic or robotic speech requires more effort when listened to. Without the emotive components in human speech, robotic speech has fewer cues to help our brains with identifying phonemes.

Nick: Do different interpretations of the Laurel/Yanny recording cast doubt on what a witness claims to have heard (ex. witness to a crime, collision, conversation)?

Mr. Joe: This question opens up a whole different Pandora’s Box. Earwitness identification, recall and the like has little to do with synthesized voices (unless of course the subject matter has to do with a synthesized voice). What one hears and perceives at the time of some acoustic event and recalls at a later time is subject to so many factors, e.g., one’s mental state at the time, how traumatic that acoustic event is, etc.

We had a case in which the reliability or trustworthiness of a witness recalling an auditory event years later was at issue. There are generally accepted academic, clinical and forensic studies in the areas of the reliability of earwitness identification. For examples, it is well-established that there is a temporal decay of memory for voices. In one study, after 2 weeks of hearing one’s voice but never seeing that person, reliability is only 68% correct, 35% correct after 3 months and only 13% correct after 5 months (less than a chance guess). The majority of forensically relevant encounters with unknown voices may well occur before the listener forms an intent to memorize.

Nick: We have no context for the Laurel/Yanny recording. Simply two words. Does context play a role in the analysis of a disputed recording? For example, a recording of a business agreement or a family law dispute.

Mr. Joe: Absolutely! Let’s take an example of the phrase “I’m going to kill you.” If that phrase appeared in a transcript with no other context, then 10 different readers may have ten different interpretations (20 if the readers are attorneys, but I digress). If that phrase was spoken in no other context and heard by someone, the emotionality and therefore the intent of that phrase alone may be revealed. If said sarcastically and sassily, then one would likely interpret that phrase without any real concerns. On the other hand, if that phrase was spoken and heard with sheer anger, then one would likely interpret that phrase with much concerns. If that phrase was in the broader context of 2 boxers, for example, being interviewed the night before their championship fight, then the meaning of that phrase is materially different than the same phrase spoken in context of 2 people viciously fighting. Clearly, one can see the context of a word or phrase can make all the difference in what was objectively meant, especially in contrast to a naked phrase with no context and completely subject to interpretation.

And another relevant issue here is the concept of top-down thinking in the context of speech perception. One can unintentionally or purposefully make someone subconsciously biased as to what s/he “should” hear in an anticipated audio recording; likewise, one’s own life experiences color what you think you hear or should hear. Stated another way, it may be equally remarkable if a study using the same “Laurel/Yanny” audio clip, the listener was asked what they hear without mentioning either or any name or word.

By the way, for the applicable analyses as described above, and given my 31 years of experience in critical listening of audio and acoustic evidence, and without any bias or top down thinking, it is clear to me that the word from the May 16, 2018 NYTimes article that the word generated is “Laurel.”


 

There you have it, folks! Laurel is the word that has baffled the Internet for the last three days. I want to extend a huge thank you to Herbert Joe of Yonovitz & Joe, LLP, for his exquisite scientific analysis of the Laurel/Yanny audio clip. What mystery will the Internet provide next? Only time will tell. When there is a mystery to solve, you can get your forensic scientific answers on this blog! Naturally, you’ll get some non-scientific analysis from yours truly.