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In my previous Excel VLOOKUP formula tutorial I mentioned that there are two ways you can use a VLOOKUP but most people know one way or the other, and only a few know both.

As promised here’s the second way to use it, and I call it the Sorted List version as it relies on the data in the table you are referencing being sorted.

Note: If you haven’t read the first tutorial, then I recommend you first watch the video below from the beginning to get an understanding of how VLOOKUP works.

Excel VLOOKUP Formula Video Tutorial

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First let’s set the scene:

In the image below we want to lookup the Commission Rates table in cells G6:I13, and find the rate in column I based on the sales values in column D, and return the result to column E.

Excel VLOOKUP Function syntax:

=VLOOKUP(

lookup_value

table_array

col_index_num,

range_lookup

)

And to translate it into English it would read:

=VLOOKUP(

find this value

in that table

return the value in the nth column of the table

find an exact match if you can, but if not, find the next lowest match

)

Note: with the Sorted List version we want Excel to find the next closest option in our table, i.e. an approximate match. To specify this we can leave the ‘range_lookup’ argument blank, or enter TRUE, or 1.

Excel VLOOKUP approximate match formula example:

Remember we want Excel to find the Commission % Rate and enter it in cell E6, so in English our formula will read:

=VLOOKUP(

find where the Sales amount $3,112

falls in the Commission Rates table G6:I13

return the value in column 3 of the table

if there isn't an exact match, find the next closest value

)

=VLOOKUP(

$G$6:$I$13

TRUE

)

Let me clarify some points:

1) ‘find where Sales amount $3,112, falls in the Commission Rates table’ – Excel doesn’t actually take into consideration column H in our table. I have simply put it there to help understand the commission ranges. Excel is in fact looking for the exact amount $3,112 in our Commission Rates table, and when it can’t find it, it finds the next best lower amount and returns the value in column 3.

3) If we had consecutive duplicates in our Commission Rates table Excel will find the last instance of the value and return the result in column 3. For example, if instead of the amount $4001 in cell G11, you had $3001 again. Excel would return the value of 6% as it’s finding the last best match for our amount. The tip here is to remove any duplicates or you’ll end up with erroneous results.

4) Unlike the VLOOKUP Exact Match version of the formula, this version requires the list to be sorted in ascending order. Just like with duplicates explained above, if it’s not sorted you will end up with erroneous results.

You’ll notice in the formula bar above there are ‘$’ signs around the reference to the table. This is called an absolute reference and it allows us to copy the formula down column E without Excel dynamically updating the table range as we copy.

Want More?

Check out my previous tutorial for VLOOKUP Rules & Common Mistakes!

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Excel Sorted Dynamic Unique List

I really wanted the title of this post to be “Excel Sorted Dynamic Unique List Ignoring Blanks and Errors”, but I didn’t want to brag 😉

It has never been so easy to extract a unique or distinct list of values in Excel than it is now that we have Dynamic Array formulas*.

*Dynamic Array formulas are only available in Office 365. I’ll provide links to an alternative for Excel 2023 and earlier versions at the bottom of this post.

Note: At the time of writing, Dynamic Arrays are only available in Office 365 and are currently in beta on the Insiders channel. We don’t have an ETA for when they will be available to all Office 365 users yet. And to be clear, Excel 2023 does not come with Dynamic Arrays. The only way to get them is with Office 365 …or wait until Excel 2023 (?) comes out.

Excel Sorted Dynamic Unique List Formula

The formula for extracting a list of sorted unique values that ignore errors and blanks is super easy.

Step 1: Format the source data in an Excel Table. That way when new rows are added, or rows removed, the formula will automatically pick up the changes.

Step 2: The formula.

The most complicated part of the formula, which isn’t really that complicated, is the FILTER function, that enables us to return the list excluding errors and blank cells, among other things. The UNIQUE and SORT functions then enclose FILTER.

The FILTER function takes the following arguments:

=FILTER(array , include, [if_empty])

The array argument is the table or range of cells you want to filter.

The include argument allows you to insert a logical test specifying which values to include.

The if_empty argument is an optional value to return if there are no records that match our ‘include’ criteria. We don’t need it in this example.

The formula is:

SORT(

UNIQUE(

FILTER(Table1[Names]

NOT(ISBLANK(Table1[Names]))

NOT(ISERROR(Table1[Names]))

)

FILTER the Names column of Table1 and return a list of values, where the Names are not blank AND the Names are not errors.

The NOT(ISBLANK(Table1[Names])) and NOT(ISERROR(Table1[Names])) formulas return a list of TRUE and FALSE Boolean values as shown below:

=SORT( UNIQUE( FILTER(Table1[Names], {TRUE;TRUE;TRUE;TRUE;TRUE;FALSE;TRUE;TRUE;FALSE;TRUE;TRUE;TRUE;TRUE}* {TRUE;TRUE;TRUE;TRUE;TRUE;TRUE;TRUE;TRUE;TRUE;TRUE;TRUE;FALSE;TRUE}) ) )

The FALSE values are discarded before passing the list to the UNIQUE function. The UNIQUE function then removes the duplicate names before passing the list to the SORT function, which sorts it in ascending order.

If you prefer the list sorted in descending order you can add ‘,,-1’ to the SORT formula like so:

=SORT( UNIQUE( FILTER(Table1[Names], NOT(ISBLANK(Table1[Names]))*NOT(ISERROR(Table1[Names])) ) )

, ,-1

)

Dynamically Update

And because I formatted the source for my Excel Sorted Dynamic Unique list in an Excel Table, when I add new names it automatically updates:

Notice how the results automatically ‘spill’ to the cells below? This is the new Dynamic Array formula functionality available to Office 365 users.

Unique Lists in Earlier Versions of Excel

If you’re not fortunate enough to have Office 365 and these handy dynamic array formulas, you can use one of the techniques described here.

Related Lessons

SORT Function – there’s more to the SORT function than I’ve demonstrated here. You can also sort multiple columns and choose which column to sort by.

UNIQUE Function – the UNIQUE function can also handle multiple columns and differentiate between unique and distinct values.

FILTER Function - you can filter more than one column and FILTER can handle OR criteria as well as AND criteria.

NOT Function – Not enables us to check if a logical test doesn’t exist.

ISBLANK Function and ISERROR Function – the IS functions check to see if a condition exists and return a TRUE FALSE, depending on the outcome. There are more IS functions at the link above.

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How To Use Vlookup In Excel

The VLOOKUP function in Excel scares a lot of people because it has a lot of parameters and there are multiple ways to use it. In this article you’ll learn all of the ways you can use VLOOKUP in Excel and why the function is so powerful.

Table of Contents

VLOOKUP Parameters In Excel

When you start typing =VLOOKUP( into any cell in Excel, you’ll see a pop-up showing all of the available function parameters.

Let’s examine each of these parameters and what they mean.

These four parameters let you do a lot of different, useful searches for data inside of very large datasets.

A Simple VLOOKUP Excel Example

VLOOKUP isn’t one of the basic Excel functions you might have learned, so let’s look at a simple example to get started.

It would be very time consuming to search through such a large dataset to find the school that you’re interested in.

Instead, you can create a simple form in the blank cells on the side of the table. To conduct this search, just make one field for School, and three additional fields for reading, math, and writing scores.

Next, you’ll need to use the VLOOKUP function in Excel to make these three fields work. In the Reading field, create the VLOOKUP function as follows:

Type =VLOOKUP(

Select the School field, which in this example is I2. Type a comma.

Select the entire range of cells that contain the data you want to look up. Type a comma.

When you select the range, you can start from the column you’re using to look up (in this case the school name column), and then select all of the other columns and rows that contain the data.

Note: The VLOOKUP function in Excel can only search through cells to the right of the search column. In this example, the school name column needs to be to the left of the data you’re looking up.

Next, to retrieve the Reading score, you’ll need to select the 3rd column from the leftmost selected column. So, type a 3 and then type another comma.

Finally, type FALSE for an exact match, and close the function with a ).

Your final VLOOKUP function should look something like this:

=VLOOKUP(I2,B2:G461,3,FALSE)

When you first press Enter and finish the function, you’ll notice the Reading field will contain an #N/A.

This is because the School field is blank and there is nothing for the VLOOKUP function to find. However, if you enter the name of any high school you want to look up, you’ll see the correct results from that row for the Reading score.

How To Deal With VLOOKUP Being Case- Sensitive

You may notice that if you don’t type the name of the school in the same case as how it’s listed in the dataset, you will not see any results.

This is because the VLOOKUP function is case sensitive. This can be annoying, especially for a very large dataset where the column you’re searching through is inconsistent with how things are capitalized.

To get around this, you can force what you’re searching for to switch to lowercase before looking up the results. To do this, create a new column next to the column you’re searching. Type the function:

=TRIM(LOWER(B2))

This will lowercase the school name and remove any extraneous characters (spaces) that might be on the left or right side of the name.

Now that all of your data is cleaned up in this new column, slightly modify your VLOOKUP function in Excel to use this new column instead of the previous one by starting the lookup range at C2 instead of B2.

=VLOOKUP(I2,C2:G461,3,FALSE)

Now you’ll notice that if you always type your search in lower case, you’ll always get a good search result.

This is a handy Excel tip to overcome the fact that VLOOKUP is case sensitive.

VLOOKUP Approximate Match

While the exact match LOOKUP example described in the first section of this article is pretty straightforward, the approximate match is a little more complex.

The approximate match is best used to search through number ranges. To do this correctly the search range needs to be properly sorted. The best example of this is a VLOOKUP function to search for a letter grade that corresponds to a number grade.

If a teacher has a long list of student homework grades from throughout the year with a final averaged column, it would be nice to have the letter grade corresponding to that final grade come up automatically.

This is possible with the VLOOKUP function. All that’s required is a lookup table off to the right that contains the appropriate letter grade for each numerical score range.

Now, using the VLOOKUP function and an approximate match, you can find the proper letter grade corresponding to the correct numeric range.

In this VLOOKUP function:

lookup_value: F2, the final averaged grade

table_array: I2:J8, The letter grade lookup range

index_column: 2, the second column in the lookup table

[range_lookup]: TRUE, approximate match

Once you finish the VLOOKUP function in G2 and press Enter, you can fill in the rest of the cells using the same approach described in the last section. You’ll see all of the letter grades properly filled in.

Note that the VLOOKUP function in Excel searches from the bottom end of the grade range with the assigned letter score to the top of the range of the next letter score.

So, “C” needs to be the letter assigned to the lower range (75), and B is assigned to the bottom (minimum) of its own letter range. VLOOKUP will “find” the result for 60 (D) as the closest approximate value for anything between 60 to 75.

VLOOKUP in Excel is a very powerful function that has been available for a long time. It is also useful for finding matching values anywhere in an Excel workbook.

Keep in mind, however, that Microsoft users who have a monthly Office 365 subscription now have access to a newer XLOOKUP function. This function has more parameters and additional flexibility. Users with a semi-annual subscription will need to wait for the update to roll out in July 2023.

Pagerank Explained In Simple Terms!

In my previous article, we talked about information retrieval and how machines can read the context from free text. Let’s talk about the biggest web information retrieval engine, Google, and the algorithm that powers its search results: the Google PageRank algorithm. Imagine you were to create a Google search in a world devoid of any search engine. What basic rules would you code to build such a search engine? If your answer is to use a Term Frequency or TF-IDF framework, consider the following case:

But, do search engines like Google face this challenge today? Obviously not! This is because they take help of an algorithm known as PageRank. In this article, we will discuss the concept of PageRank. In the next article, we will take this algorithm a step forward by leveraging it to find the most important packages in R.

An artificial web world

Imagine a web which has only 4 web pages, which are linked to each other. Each of the box below represents a web page. The words written in black and italics are the links between pages.

For instance, in the web page “Tavish”, it has 3 outgoing links : to the other three web pages. Now, let’s draw a simpler directed graph of this ecosystem.

Here is how Google ranks a page : The page with maximum number of incoming links is the most important page. In the current example, we see that the “Kunal Jain” page comes out as the most significant page.

Mathematical Formulation of Google Page Rank

First step of the formulation is to build a direction matrix. This matrix will have each cell as the proportion of the outflow. For instance, Tavish (TS) has 3 outgoing links which makes each proportion as 1/3.

Now we imagine that if there were a bot which will follow all the outgoing links, what will be the total time spent by this bot on each of these pages. This can be broken down mathematically into following equation :

A * X = X

Here A is the proportions matrix mentioned above

X is the probability of the bot being on each of these pages

Clearly, we see that Kunal Jain’s page in this universe comes out to be most important which goes in the same direction as our intuition.

Teleportation adjustments

Now, imagine a scenario where we have only 2 web pages : A and B. A has a link to B but B has no external links. In such cases, if you try solving the matrix, you will get a zero matrix. This looks unreasonable as B looks to be more important than A. But, our algorithm still gives same importance for both. To solve for this problem, a new concept of teleporatation was introduced. We include a constant probability of alpha to each of these pages. This is to compensate for instances where a user teleports from one webpage to other without any link. Hence, the equation is modified to the following equation :

(1-alpha) * A * X + alpha * b = X

Here, b is a constant unit column matrix. Alpha is the proportion of teleportation. The most common value taken for alpha is 0.15 (but can depend on different cases).

Other uses of PageRank Algorithm & End Notes

In this article we discussed the most significant use of PageRank. But, the use of PageRank is no way restricted to Search Engines. Here are a few other uses of PageRank :

Finding how well connected a person is on Social Media : One of the unexplored territory in social media analytics is the network information. Using this network information we can estimate how influential is the user. And therefore prioritize our efforts to please the most influential customers. Networks can be easily analyzed using Page Rank algorithm.

Fraud Detection in Pharmaceutical industry : Many countries including US struggle with the problem of high percentage medical frauds. Such frauds can be spotted using Page Rank algorithm.

Understand the importance of packages in any programming language : Page Rank algorithm can also be used to understand the layers of packages used in languages like R and Python. We will take up this topic in our next article.

Thinkpot: Can you think of more usage of Page Rank algorithm? Share with us useful links to leverage Page Rank algorithm in various fields.

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Scandal At Danske Bank Explained

The scandal at Danske Bank has been described as one of the most significant money-laundering operations that Europe has ever witnessed.

Years of wrongdoing were followed by years of watchdog probes and international condemnation. But this week, the saga has concluded – in the form of a vast monetary penalty and more scathing criticism from US watchdogs.

The bank hopes to draw a final line in the sand on its most turbulent period in history. It all depends, though, on whether it can learn from its governance failures.

Quick recap

In 2023, it emerged that Danske Bank had allowed over €200 billion in suspicious transactions to move through its channels.

The action centred on the bank’s Estonian branch (now closed). Ten former employees of that branch were arrested. Then-Danske Bank CEO Thomas Borgen resigned.

Multiple watchdogs – chiefly Danish and US authorities – have been conducting an extensive probe of the bank ever since.

This week, the bank announced a final settlement worth over €2 billion with those authorities and accepted “full responsibility for the unacceptable failures and misconduct of the past, which have no place at Danske Bank today.”

Why is governance at the heart of this scandal?

Because anti-money laundering protocols begin at the top levels of a business. That responsibility only increases when the business in question is one of the most prominent banks in Europe.

Principles and processes start with organisational strategy and filter down. Over the past several years, we have seen that this simply didn’t happen at Danske Bank.

Whether Danske Bank’s strategy was inadequate or simply ignored makes no difference now; its board and the executive team failed to give proper oversight. Now they are paying the price.

If senior leaders didn’t facilitate money laundering themselves, they ignored red flags showing that others were doing so. This, in the eyes of government watchdogs, signals culpability. New laws mean that it’s becoming harder to hide from that fact.

What has the scandal at Danske Bank shown about its governance?

At the heart of the issue was Danske Bank’s willingness to lie as part of its governance strategy. At least, that’s how US authorities see it.

Much of the money attached to the scandal ultimately ended up moving through other banks based in the US, and because of this, Danske Bank has been accused by the US Department of Justice (DOJ) of “deceiving” these banks.

“By at least February 2014, as a result of internal audits, information from regulators, and an internal whistleblower, Danske Bank knew that some NRP customers were engaged in highly suspicious and potentially criminal transactions,” a US Department of Justice (DOJ) statement said this week.

“Danske Bank also knew that Danske Bank Estonia’s anti-money laundering program and procedures did not meet Danske Bank’s standards.”

So, senior leaders knew what was happening and didn’t say anything?

Yes, and also, they didn’t act sufficiently to stop wrongdoing.

You’ll notice that the DOJ accused the bank of inaction in 2014 – in other words, three years before the scandal’s impacts began to unfold in the public realm and two years before the dirty money stopped flowing.

No corporate governing body should allow their company to fall into such reckless law-breaking. But pivotally, no governing body should allow their company to remain in that state. Danske Bank did, and now it is paying the price.

What governance lessons can we learn from the Danske Bank debacle?

In financial institutions, boards and executive teams have a crucial duty to ensure sufficient anti-money laundering (AML) controls. Watchdogs are as eager as ever to uncover such wrongdoing and turn it into an international example.

Corporate leaders must respect and act on internal audits, especially when they raise red flags.

Action and inaction bring similar consequences. Whether a board facilitates laundering or stands by while it occurs, the responsibility falls on their shoulders.

Look at the UK as an example of toughing legislation. A proposed law there specifically suggests jail time for directors if their company facilitates financial crime.

In summary

The scandal at Danske Bank is one of the biggest money laundering cases ever uncovered. Lawmakers have blasted it and vowed harsh responses should it ever happen again.

Boards and executives in financial institutions should pay close attention to this and their companies’ channels.

If those channels are being used to move dirty money, expect a fallout.

Audio Terms Explained: Crunchy? Warm? Punchy?

Original article: August 8, 2023: Our sister site SoundGuys has all sorts of objective ways to talk about audio, and when we feature its headphones reviews, we appreciate that. But if you head to other corners of the web, you’ll find many terms used to describe audio: “warm,” “crisp,” “punchy,” “sharp,” “dull,” and more. What do these terms even mean, though? Is there some standard, or are they being used on an ad-hoc basis?

Here’s a spoiler: among enthusiasts, audio terms usually don’t have a standard, but there are standardized ways to talk about audio.

Common audio terms and what they might mean

Zak Khan / Android Authority

Even if the terms you see flying around don’t inherently mean much, we can attempt to pick apart what they might mean in a few contexts. Keep in mind that we can’t speak with every author in mind, nor can we assume consistent usage of these terms elsewhere.

What does crunchy audio sound like?

This term could have any number of meanings, but it is almost always negative. “Crunchy” sound often refers to poor reproduction and reproduction of instruments. When audio is “crunchy,” it can be difficult to tell a guitar apart from a harp and even a drum. It could sound as if everything is “crunched” together.

Crunchy may also mean the drivers are loose or broken, leading to “crackling” or “rattling” sounds in a pair of headphones or a speaker.

What does warm mean when discussing how headphones sound?

“Warm” is usually a positive term. It tends to mean that an audio product produces pleasing amounts of bass — but not too much! Warmth also implies that vocals are clear, if present, and that the mids remain audible. What usually distinguishes it from “balanced” is the presence of stronger bass than you’d find in a product called “balanced,” with highs that, while present, are less loud than the mids and lows. By extension, warmth tends to associate with clearly reproduced instrumentation.

In audiophile circles, warmth is associated with tube amplifiers and analog, versus digital, sound circuitry. However, there’s another debate about whether casual listeners can perceive any effect.

What makes music sound lush?

The term “lush” is usually a positive descriptor used for audio products that are “warm” and generally pleasant to hear. This is a slippery term. You may often see it in phrases such as “lush strings,” used to indicate both accurate instrument reproduction and an enjoyable frequency response.

How do you describe something that sounds muddy?

Bose

The term “muddy” ends up being an umbrella term for many kinds of “bad” audio. Muddy sound is usually used to describe products that don’t reproduce instruments clearly, have way too much bass, and make it difficult to pick out vocals. While it is hard to state the exact reason a writer might describe any one product as muddy, we feel safe saying it’s a negative term and generally indicates poor-quality sound reproduction.

What kind of sounds make music sparkle and shimmer?

These are terms you’ll find concerning high-frequency sound reproduction. Overall these are positive and tend to mean sound with loud high notes that aren’t too harsh or piercing. Often, writers may call cymbals or small bells “shimmery” or “sparklingly clear.” Some listeners, however, may not enjoy such loud and prominent high notes.

Is there a difference between clean, clear, and transparent audio?

These terms tend to describe audio that has instruments easily distinguishable from one another without anything sounding too loud or too quiet. It does not necessarily indicate a studio headphones-type frequency response, though. Sound can be “transparent” or “clear” and still have boosted bass if you can still hear loud strings and bells, for instance. “Clean” audio is usually the opposite of “muddy.”

Is boomy the same as bass-heavy?

“Boomy” bass is bass that’s too loud in a bad way, most often. It “booms” louder than other sounds and drowns out other frequencies.

Is thumpy sound a good thing?

Often denoted as what a subwoofer feels like, “thumpy” bass is used as a positive to indicate you can “feel” the bass notes in your body. It may also be a negative because too much bass emphasis can make it hard to hear higher-pitched frequencies. Generally, thumpy bass means a pleasing amount of bass output without being too overwhelming.

What do detailed and analytical mean when describing sound?

“Detailed” or “analytical” sound tends to mean no frequency range overpowers another so that you can hear all of them roughly equally. You might see this term come up when describing audio products for studio settings, where you’d want to hear every frequency you can. Similar to “clear,” it doesn’t necessarily beget a studio-like frequency response. Amped-up bass can still permit you to hear other frequencies if done properly.

What does it mean if mids are recessed, restrained, or hollow?

We’re lumping these together because they tend to describe similar effects, though often at different points in the audible spectrum. Sound that is “hollow” or “recessed” has mids that are too quiet. This may also be called “v-shaped,” because the frequency response chart will appear as if a big valley is present in the mids. This can make the bass and treble sound louder, but it makes vocals and other midrange frequencies harder to hear. Sometimes headphones do this because it sounds decent if you’re just trying a pair before purchase, and you may not notice the problems until a little later.

Muddy sound is usually used to describe products that don’t reproduce instruments clearly, have way too much bass, and make it difficult to pick out vocals.

Restrained can imply the same thing, but it may be more value-neutral. “Restrained bass” could be a compliment indicating the bass was expected to drown out other sounds but ended up not doing so.

When something is too loud, does that make it harsh, grating, or piercing?

Almost always indicators of problems, these terms tend to describe the high-frequency reproduction of an audio product. If the highs are too loud, it may sound like a smoke alarm or car anti-theft warning. A “grating” sound may also imply an extended or chronic problem — it makes you “grit your teeth and bear it” — while “piercing” may indicate shorter durations of the same. “Harsh” tends to be a general audio descriptor of too much treble.

What does dull, flat audio sound like?

“Dull” and “flat” might be used to describe a lack of treble notes, or they may be terms for generally “bad” audio. Its counterpoints are usually “exciting” or “fun.”

Flat might be a positive if you’re looking for studio headphones because a “flat” frequency response curve doesn’t emphasize any part of the audible spectrum too much.

What do dry, thin, liquid, and smooth mean?

“Thin” audio is usually audio that has quiet bass and sub-bass, as is “dry” audio. Liquid sound usually has audible bass, but it may be a touch too loud to hear midrange and treble instrumentation clearly like you would with something that sounds “detailed” or “analytic.”

Smooth is similar, but may also indicate no odd peaks in the frequency response curve of a product.

Does peaky audio mean music sounds too loud?

“Peaky” audio, as the name implies, tends to be used for products with frequency response curves with peaks or valleys in odd places. These can create a jarring listening experience with unexpectedly loud or quiet notes when slightly higher or lower frequencies aren’t reproduced in such a manner. Of all the casual audio terms, this one tends to be the most consistent.

What makes music sound fun or energetic?

When used to refer to dynamic range, or the difference between the loudest and most quiet parts, “energetic” implies a broad range. However, “fun” and “exciting” are far more subjective. They mean, for example, emphasized bass output, the ability of a speaker to get very loud overall, or even a particular case design.

What is the standardized audio definition of punch?

The ITU defines punch as “whether the strokes on drums and bass are reproduced with clout, almost as if you can feel the blow. The ability to effortlessly handle large volume excursions without compression (compression is heard as level variations that are smaller than one would expect from the perceived original sound).” Fair enough, but what does that signify when you’re listening to something?

First, let’s start with “compression” (also defined by the ITU) — not to be confused with audio file format compression. Audio that is “compressed” means it doesn’t have a wide dynamic range. That is, the difference between quiet and loud portions is narrow. Thus, “punchy” bass has an ample difference between quiet and loud drums, for instance. “Clout” means a heavy blow or impact. Adding that gives us bass that sounds like a drummer has made heavy, hard hits from sticks onto drums in a song.

All of these ITU standard terms get real definitions, and we can use them consistently.

A product with “punch” can handle large volume outputs without extra dynamic compression. The audio output does not all occur at one volume, and it does not blend various bass-producing instruments into a mass. In popular parlance, however, punch often has a broader definition. In this usage, it means bass that is forceful and quick.

What are the standardized audio definitions of dark and bright?

Dark audio has too much bass or not enough treble, and bright audio has too much treble or not enough bass. This is how the ITU defines them, and in general, it seems most of the time, other writers use these terms in this way. However, “bright” is also used by other publications as a compliment, so unless you’re sure a given writer is following ITU standards, this may vary.

What is the standardized audio definition of attack?

What is the standardized audio definition of boomy?

We saw this one before, but to the ITU, it specifically indicates bass that reverberates “as sound in a large barrel.” By “reverberates,” the ITU means the bass persists for too long and keeps going even after the instrument producing it is no longer being played. This is similar to the casual use of the term and indicates too much bass.

What is the standardized audio definition of dry?

Dry has a specific meaning to the ITU, where it indicates a space that does not have much reverberation. These are usually “small furnished spaces such as living rooms or spaces outdoor without reflecting objects.” Unlike its colloquial meaning, the opposite to dry in the ITU specifications is not “liquid.”

What is the standardized audio definition of tinny?

The term “tinny” is another popular option, and the ITU specification describes it as something with too much high-frequency or high-frequency response with too much resonance. You can think of it as the upper note version of “boomy.”