Apes, Gabener Nyebrang di Zebra Cross Sendirian, Pejalan Kaki Minggir Maksimal, Koplak
Gubernur DKI Jakarta, Anies Rasyid Baswedan terlihat sendirian nyebrang di zebra cross sementara para pejalan kaki kompak menepi sampai keluar zebra cross. Anies mungkin berharap ada yang nyamperin, minta selfie atau ajak foto bareng tapi nyatanya enggak.
Dia ngeloyor sendiri sementara pejalan kaki yang lainnya menepi maksimal dengan ekspresi senyam senyum, ketawa-ketiwi yang lainnya cuek bebek, EGP, parah banget Cuy! Padahal dia adalah Gubernur Indonesia yang bahkan dipuji Rizal Ramli sekelas jenderal tapi kok tak ada yang tertarik berfoto bersama.
Dari foto tersebut ini adalah kejadian kemarin saat peninjauan pembuatan pelican crossing yang berada tidak jauh dari Bundaran Hotel Indonesia (HI) Jalan MH Thamrin, Jakarta Pusat.
Aura negatif dari sang pemimpin yang selalu menimbulkan kehebohan dan kebijakan kontroversial ini membuat rakyat jadi tak simpatik. Apalagi sikapnya yang nyinyir dan nyindir pemimpin sebelumnya menambah aura negatif melekat membuat rakyat ogah mendekat. Ditambah aura Kali Item (Komentar Lanina di kolom Disqus, wkwk).
Momen yang seharusnya bisa jadi modal pencitraan di Instagram akhirnya batal dan buyar karena semua pejalan kaki pada minggir, entah karena alergi atau ilfil melihat sosok yang satu ini tiba-tiba muncul.
Tapi warga pejalan kaki itu kompak bersama menepi sembari hepi dan membuat jarak yang besar dengan sang Gubernur. Ini adalah simbol pemimpin yang berjarak dengan rakyat maka rakyat juga akan memasang jarak dengannya.
Tak ada yang mau menyerbu mendekat, selain beresiko gak mau ditabrak bareng Gubernur tapi ini natural, pejalan kaki ini jelas tak antusias melihat ada penampakan Gubernur yang tiba-tiba menyebernag bareng.
Pemimpin yang dicintai rakyat akan membuat rakyat antusias mendekat dan merapat seperti pak Jokowi dan Pak Ahok. So pasti keduanya itu akan diajak selfie, wefie dan langsung live di facebook atau Insta story.
Tapi gubernur zaman now, sepi, menyendiri dan ditinggalkan. Dia hanya bisa menatap dengan tabah ke depan ingin segera sampai secepat-cepatnya. Sementara pejalan kaki yang lain ngakak dan ketawa sembari yang lain nggak enak akhirnya tertawa dalam hati.
Begitulah momen cuplikan foto itu sudah berbicara banyak, nanti pemujanya pasti akan membela junjungannya setengah mati. Seharusnya pendukungnya kompak untuk beramai-ramai nyebrang zebra corss bareng Gubernur, hehe.
Sambutan tak antusias warga yang melihat Gubernur menegaskan warga DKI itu tidak bahagia dengan kehadirannya bahkan perihnya, tak dianggap. Siape luh, katanya! Malah warga hepi sendiri seolah mengatakan, sorry kami nggak butuh loe, Governor! Mereka malah menepi dan menjauh. Gubernur juga terpaksa pasrah sembari mengeraskan hatinya untuk tabah sampai ke seberang jalan.
Pemandangan ini menunjukkan ironi pemimpin yang seharusnya peduli dan dicintai pasti dan otomatis akan menjadi magnet bagi rakyatnya. Ini pemimpin yang rupanya magnetnya terbalik jadi malah pada menjauh semua.
Aura negatif yang semakin tebal itu membuat dirinya juga jadi tebal muka dan tebal hati untuk setiap masukan dan koreksi yang diberikan oleh berbgaai pihak. Pemerintah Pusat sebagai atasannya juga dicuekin, membuat dirinya makin sombong dan arogan.
Upaya menghadirkan dua pelican crossing yang dibangun di sisi Utara dan Selatan Jalan MH Thamrin tepatnya didepan gedung Hotel Pullman itu memang untuk kepentingan praktis pengguna jalan. Mempercepat penyeberangan tapi malah efeknya menambah macet. Pelican cross ini sebenarnya bukanlah hal baru, sudah pernah ada di Indonesia.
Pelican crossing sendiri hampir sama dengan zebra cross, hanya saja dilengkapi dengan lampu lalu lintas, tombol penyeberangan dan pengeras suara. Sementara pada dua pelican crossing sudah dibuka hari ini.
Dalam prakteknya pelian cross itu menimbulkan kemacetan dan waktu menyeberang yang terlalu singkat. Ini peru menjadi catatan dalam pelaksanaannya apalagi kalau ada ibu hamil atau orang yang sudah tua menyebernag, kan kasihan.
Menurut Anies, untuk sementara pihaknya akan menyiagakan petugas Dinas Perhubungan (Dishub) dengan tujuan membiasakan pejalan kaki dan pengguna jalan dengan pelican crossing.
“Karena itu petugas hadir untuk memberikan rasa tenang, pada saat mereka menyeberang. Menyeberang jalan di Indonesia ini menegangkan. Karena itu mereka (Dishub) hadir untuk membantu supaya mereka (pejalan kaki) tenang karena ada petugas. Petugasnya ada 24 jam,” ujar Anies.
Menegangkan karena ada Gubernur yang membuat kebijakan yang ajib dan aneh-aneh, haha, jadi tegang deh pejabat Anda karena sewaktu-waktu bisa dipecat. Menegangkan juga karena waktu penyeberangan Cuma 15 detik Gabener, kalau jalannya lambat bisa ditabrak tuh, wkwk.
Ronindo
Addicted to spicy food. Favorite quote : The best revenge is not to be like your enemy - Marcus Aurelius
Sure, those things help, but they don’t skyrocket your rankings. When you build links, it can take months if not a year for them to kick in.
And everyone is doing on-page SEO, so there is nothing unique about it anymore.
So, what do you think it is? Shall I give you a hint?
The accidental SEO hack
I stumbled on the “future” of SEO by accident. Back in March 2016, I was able to take my traffic from 185,980 visitors a month to 195,596 a month.
And it all happened within 30 days.
Here was my traffic in February 2016:
After I ran my accidental marketing experiment, my traffic grew by 9,616 visitors (to 195,596 monthly visitors in March).
I know what you are thinking… there are more days in March than February. And although that’s true, the majority of those additional 9,616 visitors came from search.
So what happened?
As I mentioned above, I accidentally stumbled upon this.
But once I noticed that the side effect of this marketing experiment was that it increased my search traffic, I ran it again.
And this time, on a much larger scale.
Let’s look at my traffic in June 2016:
And now let’s look at July 2016:
And now look at August 2016:
That growth rate is ridiculous! I grew my traffic to 454,382 visitors a month in August from 240,839 in June!
See, during that time period, I wasn’t trying to figure out any cool SEO hacks that would boost my rankings… it just accidentally happened. And it happened because I was running a marketing experiment that wasn’t related to SEO, but funny enough, it impacted SEO (in a major way!).
As you can see from the graphs above, I was able to drastically boost my rankings and search traffic over time.
So, can you guess what it was?
Let me give you a hint…
How Google deals with the Internet cesspool
The EX-CEO of Google, Eric Schmidt, talked about how the Internet is becoming a place where false information is thriving. Essentially, the Internet is becoming a cesspool.
He went on to discuss how brands were becoming more important signals whether or not content can be trusted.
And in his words:
Brands are the solution, not the problem. Brands are how you sort out the cesspool.
In other words, if you want to do well in the long run, you have to build a brand.
When you look at Google you can see clearly that it’s dominated by big brands. From Huffington Post to Wikipedia to CNN… the list goes on and on.
Sure, these sites have a lot of content and backlinks, but they also have huge brands.
When my traffic grew from 185,980 visitors a month in February 2016 to 454,382 visitors in August, it was due to one thing.
My brand kept growing!
Just look at the brand queries for my name over time according to Google Trends:
Over time, my brand has grown in popularity. And as it’s grown, so has my traffic.
In the last 28 days, 40,412 people found my site by Googling variations of my name.
That’s a lot of people!
But what’s cool is, the traffic increases didn’t mainly come from people Googling “Neil Patel.” It mainly came from an increase in rankings for non-branded terms like “online marketing.”
It’s so effective that I generate over a million visits from Google each month now:
To clarify, the way Google looks at brands is that if a website gets a higher amount of brand queries than their competition (the number of people searching for your website name each month), it tells Google that people prefer that one brand over another.
And when Google is determining where to rank a website for all of the terms they are optimizing for, they give more preference to the ones with the most popular brands because those are the sites that people prefer more.
So why does Google put so much emphasis on brands verus other search signals?
Why Google loves brands
Just think about it, it’s the hardest thing to manipulate.
You optimize your on-page code with very little effort these days.
Heck, if you have a WordPress blog you can just use the Yoast SEO plugin and it will do a lot of the work for you.
Now, I am not saying you should leverage all of these link building tactics because Google frowns upon many of them and they are short-sighted (always think long-term).
You get the point… it’s not that hard to build links these days if you know what you are doing.
But the one thing that is hard to build, no matter how good of a marketer you are, is a brand.
Even if you do massive PR stunts, which causes everyone to know your brand and search for your brand on Google (that’s how they measure it), it won’t help you in the long term.
And trust me, I’ve tried it all.
I even tried to get people to search for my name by having famous people hold up signs with my name as it causes others to wonder “who is Neil Patel” and perform a Google search. I also did that throughout the world in different languages.
I even had Larissa Manoela, a famous Brazilian actress, post this on her Instagram account for her 15+ million (million!!) followers.
The concept behind this marketing stunt was that no matter what industry you are in, everyone follows celebrities (or at least knows about them). And if you can get these celebrities to talk about you, it will create buzz and get new people to learn who you are and potentially become an avid follower. Or at the very least, search for you in Google.
And if you can get a lot of celebrities (or social influencers) to talk about you during the same time, it will create even more buzz and potentially cause newspapers and news websites to talk about you as well.
Now I didn’t have enough money to pay A-list celebrities, so I took Internet celebrities (and a few big names in countries outside of the US) and got them to hold up signs with my name on both Facebook and Instagram.
This created buzz, which then caused more people to Google my name. This, in turn, increased my popularity over time. And the end result was that I increased my rankings for non-branded terms (like “online marketing” and “SEO”).
That’s how I got the big boost in traffic from February 2016 to August 2016.
Although that will help boost your search traffic in the short run, it won’t last long unless you continually build up your brand. Google is looking to see how many people are searching for your brand name on a daily basis… and ideally, they want to see this increase over time.
In other words, if you can’t maintain your brand’s popularity, your search traffic will die off if you use short-term strategies as I did. That’s why you see huge spikes in my brand when you look at the Google Trends image below.
But if your brand continues to grow in popularity, so will your search traffic for all of your non-brand related terms.
It’s hard to see it in the chart above, but before I focused on building my brand, I was only generating 18,304 brand queries per month, versus 40,412 that I am generating now.
So how do you build a brand?
As I mentioned above, you need people searching for your brand name on a consistent basis.
The only way to really do this is by creating value.
Just look at me… I blog on a regular basis, produce educational videos, I have a daily podcast, and I even speak at conferences.
All in all, it has caused my brand to grow over the years.
And this works even better for corporations. If you create an amazing product or service, people will love your brand and keep coming back.
I learned this from my Ubersuggest acquisition. When I bought the brand and merged it into my website, my number one search query become the term “Ubersuggest” and variations of it.
People love the tool… so much so that they access it by Googling the brand name. Sure, the tool has more direct traffic, but people also go to sites using Google.
But to get back to the question of how you can build a brand?
Well, there are no very detailed strategies I can give you as it will range from business to business. I can give you an overview of strategies that have worked for me though, as well as some stats to go along with it:
Blog weekly
I’ve found that if you blog on a regular basis you get more brand queries.
When people are expecting content from you on a regular basis, they’ll Google your brand to come back to your blog and read your latest content.
When I blogged daily, I generated 11% more brand queries than when I blogged once a week. This is why sites like CNN, Huffington Post, Business Insider, and every other news site generates a lot of brand queries… they blog numerous times per day.
Create videos
You don’t have to copy my YouTube strategy, but you should create some sort of videos related to your product, service, or industry. Not because of Google or YouTube, but because of social networks like Facebook and LinkedIn love video content.
So much so that it’s easier to get eyeballs on Facebook and LinkedIn for video content than it is on YouTube.
This will cause more people to see your brand, and build a relationship with you or your company.
What I’ve found is that the more videos I create the more brand queries I get. Just look at the screenshot below:
The screenshot shows how many views my videos received on YouTube over the last 28 days from people searching for my name. It’s 3,806 visitors to be exact.
I know YouTube brand queries doesn’t mean more brand queries on “Google.”
But if you can push out video content on YouTube, Facebook, and LinkedIn, it can’t hurt. It will cause more people to see your brand, and eventually, this should cause more people to Google you.
Now, the reason I am emphasizing LinkedIn and Facebook is that it is easier to generate views on those two social networks for video content. I know they count views differently, but there is a huge difference (and even if there weren’t, it’s extra views).
Just look at my YouTube views for my video on GoogleRank Brain, it has 10,010 views:
And on Facebook it has 31,000 views:
And on LinkedIn it has 29,506 views:
So if YouTube is creating roughly 3,806 brand queries per month when it’s generating fewer views than Facebook and LinkedIn, just imagine what these videos are doing for my brand.
Sadly, Facebook and LinkedIn don’t share stats in the same way as YouTube, but you can come to the conclusion that it probably helps in a similar fashion.
That’s why you need to create videos in order to promote your personal or corporate brand on all social sites (you can use the same content, just upload it to each social network).
Speak at conferences
Every time I speak at conferences I see an influx of brand queries.
It’s harder for me to see these days as I already have a lot of brand queries, but I used to see big swings in my brand queries when I was starting out because of my participation at conferences.
Every time I spoke at a conference with at least 300 attendees (the number of people attending your speech, not the total number of people registered for the event), I would see an increase in brand searches within 24 to 48 hours of my talk.
Each speech would typically bring me 110 to 180 extra brand queries. Although that seems high, you have to keep in mind that reporters also sit in on speeches and are blogging about your speech. This creates more press related to you and your company, which helps with brand queries.
And if the conference you are speaking at uploads the video of your speech to YouTube (or even live streams the event on Facebook) you’ll see even more brand queries.
The larger the audience the better as it creates more potential searches. If you don’t know how to get speaking spots, check this out.
And if you don’t have the time to travel, you can speak at virtual events. They won’t have the same effect, but it is better than nothing.
Build an amazing product or service
I learned this one from my Ubersuggest acquisition… if people love what you are building, your brand queries will really skyrocket. It’s so effective, that it has become my new SEO strategy.
As you can see, the better product you build, the more brand queries you’ll receive.
With Ubersuggest I took a simple approach, just take what my competitors are charging for and give it away for free.
And my brand queries don’t even compare to companies like Dropbox, Apple, Slack, and the loads of other companies that have built amazing products or service.
This strategy is easy to replicate and you’ll see the results fast as long as you take what your competition is charging for and give it away for free.
Just look at the chart above: it shows a huge spike in just 1 month. That was when I released more features for free.
Performance-based press
There are companies like PRserve that charge for performance-based press. If they get you press, you then pay. If not, you don’t pay a dime. It won’t cause tons of brand queries at first, but over time it will help.
If you want to do it yourself, here is an article I wrote breaking down how to get press. It takes longer and it’s harder than hiring someone, but as long as you are willing to put in the time, you will see results.
You can also check out sites like Help a Reporter Out, where journalists ask questions and people go to help them out. When you see a question related to your expertise or industry, you should respond and you can get free press.
Release a book
This works better for personal brands, but publishing a book is a great way to get more brand queries. There are even companies that can streamline the whole process for you.
When I released my book Hustle, I learned three important things:
Don’t co-author a book – I love my co-authors, but I would have received much more of a brand boost if I self-authored the book.
Write a book about your expertise – Hustle was a mainstream book that appealed to most people versus people who wanted to learn about marketing. If I wrote a book about marketing, which is where my expertise is, I believe my brand would have grown faster (even if fewer people purchased the book).
Don’t focus on being a New York Times Bestselling author – I was on the list 3 weeks in a row, and I don’t think it did much for me. Focus on building a following within your space, versus just generating book sales from people who don’t care about your business.
Hopefully, the strategies above will give you a start on building your brand… it just takes time and a lot of elbow grease.
There is no quick solution and what worked for me may not work for you. So get your creative juices flowing and think outside the box.
Conclusion
Branding may seem like a waste of money, but it isn’t.
I used to think companies like Nike were wasting money with all of their TV ads when they could have focused on channels that produced a direct ROI like Google Ads.
But what’s funny is, when you think of shoes you naturally think of “Nike.” You don’t have to Google them, you just know about them because they’ve built a huge brand and are everywhere.
Same goes for Visa. When you think of credit cards, Visa comes to mind because they are accepted worldwide and run tons of ads.
The list keeps going on and on… from McDonald’s to Coca-Cola… the one thing you have to learn from these big companies is that you have to build an amazing brand. Not only will it create more brand searches, but it will help drive more revenue in the long-run.
Most of the companies I mentioned above don’t generate the majority of their sales from Google… they generate their sales from having a huge brand that people trust and love. The brand queries that they get on Google is just an added benefit.
And if that doesn’t convince you, here is an interesting stat. One of my friends works for one of the largest travel companies in the world. They are publicly traded and run television ads as well as spending millions on Google/Facebook ads each month.
When they run TV ads, their Google cost per click (CPC) goes down by roughly 20% because people are seeing their brand everywhere and are more willing to click on it. When they turn off the TV ads, they see the CPCs go back up.
They also own so many travel sites in the space, so they tested this out with a handful of them. Every time they saw similar results, no matter which travel site they tested it on.
More money spent on branding equals a cheaper CPC. When they don’t run TV ads, CPCs go up.
I know you probably don’t like the idea of branding because it isn’t something that is instant, and it is hard to manipulate. But that’s why creating a strong brand drastically increase your non-branded rankings.
So, what are you waiting for… are you going to focus on building a brand?
This is the first post in a series on Automatic Speech Recognition, the foundational technology that makes Descript possible. We’ll be exploring the current state of the industry, where it’s heading — and, in this installment, where it’s been.
Descript is proud to be part of a new generation of creative software enabled by recent advancements in automatic speech recognition (ASR). It’s an exciting time: the technology recently crossed a threshold that sees it trading its longstanding promise for remarkable utility, and it’s only getting better.
This moment has been a long time coming. The technology behind speech recognition has been in development for over half a century, going through several periods of intense promise — and disappointment. So what changed to make ASR viable in commercial applications? And what exactly could these systems accomplish, long before any of us had heard of Siri?
The story of speech recognition is as much about the application of different approaches as the development of raw technology, though the two are inextricably linked. Over a period of decades, researchers would conceive of myriad ways to dissect language: by sounds, by structure — and with statistics.
Early Days
Human interest in recognizing and synthesizing speech dates back hundreds of years (at least!) — but it wasn’t until the mid-20th century that our forebears built something recognizable as ASR.
1961 — IBM Shoebox
Among the earliest projects was a “digit recognizer” called Audrey, created by researchers at Bell Laboratories in 1952. Audrey could recognize spoken numerical digits by looking for audio fingerprints called formants¹ — thedistilled essences of sounds.
In the 1960s, IBM developed Shoebox — a system that could recognize digits and arithmetic commands like “plus” and “total”. Better yet, Shoebox could pass the math problem to an adding machine, which would calculate and print the answer².
1961 — A demonstration of IBM’s Shoebox
Meanwhile researchers in Japan built hardware that could recognize the constituent parts of speech like vowels; other systems could evaluate the structure of speech to figure out where a word might end. And a team at University College in England could recognize 4 vowels and 9 consonants by analyzing phonemes, the discrete sounds of a language¹.
But while the field was taking incremental steps forward, it wasn’t necessarily clear where the path was heading. And then: disaster.
October 1969 —The Journal of the Acoustical Society of America
A Piercing Freeze
The turning point came in the form of a letter written by John R. Pierce in 1969.
Pierce had long since established himself as an engineer of international renown; among other achievements he coined the word transistor (now ubiquitous in engineering) and helped launch Echo I, the first-ever communications satellite. By 1969 he was an executive at Bell Labs, which had invested extensively in the development of speech recognition.
In an open letter³ published in The Journal of the Acoustical Society of America, Pierce laid out his concerns.Citing a “lush” funding environment in the aftermath of World War II and Sputnik, and the lack of accountability thereof, Pierce admonished the field for its lack of scientific rigor, asserting that there was too much wild experimentation going on:
“We all believe that a science of speech is possible, despite the scarcity in the field of people who behave like scientists and of results that look like science.” — J.R. Pierce, 1969
Pierce put his employer’s money where his mouth was: he defunded Bell’s ASR programs, which wouldn’t be reinstated until after he resigned in 1971.
Progress Continues
Thankfully there was more optimism elsewhere. In the early 1970s, the U.S. Department of Defense’s ARPA (the agency now known as DARPA) funded a five-year program called Speech Understanding Research. This led to the creation of several new ASR systems, the most successful of which was Carnegie Mellon University’s Harpy, which could recognize just over 1000 words by 1976.
1976 —CMU’s Harpy Speech Recognition System
Meanwhile efforts from IBM and AT&T’s Bell Laboratories pushed the technology toward possible commercial applications. IBM prioritized speech transcription in the context of office correspondence, and Bell was concerned with ‘command and control’ scenarios: the precursors to the voice dialing and automated phone trees we know today¹.
Despite this progress, by the end of the 1970s ASR was still a long ways from being viable for anything but highly-specific use-cases.
This hurts my head, too.
The ‘80s: Markovs and More
A key turning point came with the popularization of Hidden Markov Models(HMMs) in the mid-1980s. This approach represented a significant shift “from simple pattern recognition methods, based on templates and a spectral distance measure, to a statistical method for speech processing”⁴—which translated to a leap forward in accuracy.
A large part of the improvement in speech recognition systems since the late 1960s is due to the power of this statistical approach, coupled with the advances in computer technology necessary to implement HMMs.⁵
HMMs took the industry by storm — but they were no overnight success. Jim Baker first applied them to speech recognition in the early 1970s at CMU, and the models themselves had been described by Leonard E. Baum in the ‘60s. It wasn’t until 1980, when Jack Ferguson gave a set of illuminating lectures at the Institute for Defense Analyses, that the technique began to disseminate more widely⁴.
The success of HMMs validated the work of Frederick Jelinek at IBM’s Watson Research Center, who since the early 1970s had advocated for the use of statistical models to interpret speech, rather than trying to get computers to mimic the way humans digest language: through meaning, syntax, and grammar (a common approach at the time). As Jelinek later put it: “Airplanes don’t flap their wings.”⁹
These data-driven approaches also facilitated progress that had as much to do with industry collaboration and accountability as individual eureka moments. With the increasing popularity of statistical models, the ASR field began coalescing around a suite of tests that would provide a standardized benchmark to compare to. This was further encouraged by the release of shared data sets: large corpuses of data that researchers could use to train and test their models on.
In other words: finally, there was an (imperfect) way to measure and compare success.
November 1990,Infoworld
Consumer Availability — The ‘90s
For better and worse, the 90s introduced consumers to automatic speech recognition in a form we’d recognize today. Dragon Dictate launched in 1990 for a staggering $9,000, touting a dictionary of 80,000 words and features like natural language processing (see the Infoworld article above).
These tools were time-consuming (the article claims otherwise, but Dragon became known for prompting users to ‘train’ the dictation software to their own voice). And it required that users speak in a stilted manner: Dragon could initially recognize only 30–40 words a minute; people typically talk around four times faster than that.
But it worked well enough for Dragon to grow into a business with hundreds of employees, and customers spanning healthcare, law, and more. By 1997 the company introduced Dragon NaturallySpeaking, which could capture words at a more fluid pace — and, at $150, a much lower price-tag⁸.
Even so, there may have been as many grumbles as squeals of delight: to the degree that there is consumer skepticism around ASR today, some of the credit should go to the over-enthusiastic marketing of these early products. But without the efforts of industry pioneers James and Janet Baker (who founded Dragon Systems in 1982), the productization of ASR may have taken much longer.
November 1993, IEEE Communications Magazine
Whither Speech Recognition— The Sequel
25 years after J.R. Pierce’s paper was published, the IEEE published a follow-up titled Whither Speech Recognition: the Next 25 Years⁵, authored by two senior employees of Bell Laboratories (the same institution where Pierce worked).
The latter article surveys the state of the industry circa 1993, when the paper was published — and serves as a sort of rebuttal to the pessimism of the original. Among its takeaways:
The key issue with Pierce’s letter was his assumption that in order for speech recognition to become useful, computers would need to comprehend what words mean. Given the technology of the time, this was completely infeasible.
In a sense, Pierce was right: by 1993 computers had meager understanding of language—and in 2018, they’re still notoriously bad at discerning meaning.
Pierce’s mistake lay in his failure to anticipate the myriad ways speech recognition can be useful, even when the computer doesn’t know what the words actually mean.
The Whither sequel ends with a prognosis, forecasting where ASR would head in the years after 1993. The section is couched in cheeky hedges (“We confidently predict that at least one of these eight predictions will turn out to have been incorrect”) — but it’s intriguing all the same. Among their eight predictions:
“By the year 2000, more people will get remote information via voice dialogues than by typing commands on computer keyboards to access remote databases.”
“People will learn to modify their speech habits to use speech recognition devices, just as they have changed their speaking behavior to leave messages on answering machines. Even though they will learn how to use this technology, people will always complain about speech recognizers.”
The Dark Horse
In a forthcoming installment in this series, we’ll be exploring more recent developments and the current state of automatic speech recognition. Spoiler alert: neural networks have played a starring role.
But neural networks are actually as old as most of the approaches described here — they were introduced in the 1950s¹! It wasn’t until the computational power of the modern era (along with much larger data sets) that they changed the landscape.
But we’re getting ahead of ourselves. Stay tuned for our next post on Automatic Speech Recognition by following Descript on Medium, Twitter, or Facebook.
Timeline via Juang & Rabiner¹
Note: The history of ASR is filled with more contributors and innovations than we can detail in this piece; we’ve covered some major milestones and included links to further reading below. If we’ve missed something vital, let us know!
Further Reading
Here are the resources that were helpful in writing this piece, some of which go into far more detail:
