Originally posted on Parallel Reading Multilanguage Books:

Portrait of Sherlock Holmes by Sidney Paget, 1891

Portrait of Sherlock Holmes by Sidney Paget, 1891

As an example of what I plan to do with the Parallel Reading project, below is a sample of a parallel English/Spanish text of the Sherlock Holmes short story “The Speckled Band,” by Arthur Conan Doyle. This is a parallel text composed from public-domain sources. Click on the link to download this free ebook in PDF format.

Abajo se encuentra el relato “La banda de lunares” en el inglés y el español en paralelo. Este es un relato ficcional de Sherlock Holmes por Arthur Conon Doyle. Haga clic en el enlace para descargar el libro electronico.

Speckled_Band_Doyle_Parallel_EngSpan

ARB — 21 March 2014

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I think a lot about assertions, things that people assert as true, very often without acknowledging their personal bias. To be fair, most of us are so immersed in our ideologies that we’re not aware of how they are compelling us toward bias.

The title of this post refers to some of the kinds of assertions I hear, by which someone states something as a fact:

  • The way things are — some assertion about fact, whether it has to do with science, economics, politics, or some other sphere. One of my favorite manifestations is when someone begins an utterance with the stark word “Fact,” followed by a colon to emphasize the factiness of what follows, then followed by an unquestioned assertion.
  • The way things were — some statement about history or the past. For example, such and such Egyptian dynasty ruled in such and such time period, or some assertion about why humans came down from the trees to live on the savanna.
  • What is true — This is really akin to the other two kinds of assertions I’m pointing to, but maybe in this case I’m thinking about an assertion that goes beyond a mere statement of some fact. Some examples might be that God exists or that he doesn’t, or that evolution is an incontrovertible fact.

An assertion might be well supported, but what I’m trying to spotlight here is the common practice of making an assertion without acknowledging the background and context surrounding the assertion and the person making it. One result is that people get into fierce arguments even though they aren’t really arguing about the same thing.

Here are some of the kinds of influences that one might make clear to provide context to an assertion:

  • The lines of evidence behind the assertion — Is the assertion based on scientific or scholarly research? Sometimes a speaker will make an assertion, basing his or her statement on the consensus within a profession or academic field. (Academic or scientific consensus doesn’t always mean the same thing as the everyday understanding of what constitutes a consensus.) One of the problems here is that there may actually be a minority that disputes the consensus view. There might be a legitimate critique that isn’t getting acknowledged when the speaker makes the assertion.
  • Assumptions — Many assertions are based in part on ideas or constructs that are taken for granted. As with lines of evidence, there might be a legitimate minority critique of a given assumption. One example would be dating a past event based on the conventional chronologies hypothesized by historians and archaeologists.
  • Definition of terms — Often people get into arguments without establishing and agreeing on the meaning of the point they are discussing. For example, people argue about whether evolution is true without coming to a prior understanding of what they mean by evolution.
  • The ideological leanings of the speaker — For someone who wants to evaluate an assertion, it could be useful to know something about the speaker’s ideological convictions. Is the speaker a theist? An atheist? A free-market fundamentalist? An eco-socialist? One problem here is that many people don’t like to admit that they subscribe to an ideology or aren’t even aware of it.
  • The speaker’s authority for making the assertion — When evaluating an assertion, it can be useful to know the speaker’s credentials.
  • The speaker’s underlying agenda — As with ideology, many speakers don’t like to own up to their agendas, which are often political or ideologically-driven.

As is often the case with this writing project, my purpose here is to set out some basic ideas with the intention of coming back later to revise and add ideas and examples.

ARB — 3 Oct. 2013

Originally posted on A. Roy King:

This article in Archaeology includes sound files of linguists telling brief stories in the reconstructed hypothetical Proto-Indo-European language.

Here’s one of the sound files — take a listen:

The story is called “The Sheep and the Horses,” which in English goes like this:

A sheep that had no wool saw horses, one of them pulling a heavy wagon, one carrying a big load, and one carrying a man quickly. The sheep said to the horses: “My heart pains me, seeing a man driving horses.” The horses said: “Listen, sheep, our hearts pain us when we see this: a man, the master, makes the wool of the sheep into a warm garment for himself. And the sheep has no wool.” Having heard this, the sheep fled into the plain.

Although his work is not well-regarded among linguists, Merritt Ruhlen has done some interesting work with tracing the origins of modern languages…

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quriosity:

A. Roy King outlines the seven metals on which civilization was built and points to some useful resources.

Originally posted on A. Roy King:

I was researching metalworking in the ancient world and came across a mention of the “seven metals of antiquity.” I found a good short summary, “A Short History of Metals,” by Alan W. Cramb, a metallurgist who is now provost and senior vice president for academic affairs at the Illinois Institute of Technology. Cramb identifies “the metals upon which civilization was based” as:

  1. Gold (ca) 6000BC
  2. Copper (ca) 4200BC
  3. Silver (ca) 4000BC
  4. Lead (ca) 3500BC
  5. Tin (ca) 1750BC
  6. Iron,smelte, (ca) 1500BC
  7. Mercury (ca) 750BC

Cramb discusses each of these metals and their history in more detail and says that

These metals were known to the Mesopotamians, Egyptians, Greeks, and the Romans. Of the seven metals, five can be found in their native states, e.g., gold, silver, copper, iron (from meteors) and mercury. However, the occurrence of these metals was not abundant and the first two metals to…

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Here’s a piece of business advice: Wherever you go, whatever you do, always act in such a way as to raise the bar.

In business, we frequently focus on competition. In the darwinian ideology, life is supposed to be about competition, and that idea often gets transferred into business. In reality, though, I think cooperation is more important in the way both life and business work.

Cooperation is much more fundamental to getting things done, and I think even competition can be seen in a way as a form of cooperation, in that when we compete, we make each other better by raising the bar.

ARB — 6 September 2013

 

I recently wrote a piece for Industry Market Trends about how U.S. manufacturing could be affected by the rising U.S. dollar — see “Rising U.S. Dollar Could Put a Damper on Manufacturing Exports.”

In my original story, I included a brief primer on what is meant by a “strong” or “weak” currency. My editor didn’t think our readers needed to know about that, but I found it hard to track down a coherent explanation of this, so I just wanted to publish here some very basic information about a topic that I found confusing. Here’s what I originally wrote:

On the face of it, one might think a “strong dollar” is a positive thing. Strength is good, right? Higher value is good, right? But that’s not necessarily the case in the world of foreign exchange. When we talk about the rising dollar, we mean that it is rising in value, or getting stronger, against other currencies.

For example, as of this writing, one U.S. dollar (USD) buys about 98 Japanese yen (JPY). In 2011, one USD was worth about 76 JPY. The dollar now buys more JPY than it did in 2011, so we would say it is stronger. However, ten years ago, the dollar was at about 110 JPY, so you could say that long-term the USD is weak against the yen.

The U.S. dollar is also measured by the U.S. Dollar Index (USDX), which is a “basket” of foreign currencies, including the Euro (EUR), the JPY, the British pound sterling (GBP), the Canadian dollar (CAD), the Swedish krona (SEK) and the Swiss franc (CHF). As of this writing, the USDX is between 81 and 82. Ten years ago, it was around 104, which means that long-term the dollar is weaker. However, in 2011, the USDX stood at around 70, so that the more recent trend is a rising dollar.

The IMT article goes on to explain how a rising dollar can affect manufacturing by making exports from the U.S. more expensive in other countries.

– ARB, 30 July 2013

I’ve been looking for a way to use speech recognition to automate the transcription of interviews, meetings, speeches, conference presentations, and so on.

I spend a lot of time on the phone interviewing experts for the articles and reports I write. Normally I conduct the interview with a headset and do my best to type a transcript of what is said. I’m slow and a terrible typist, so my transcript misses a lot and comes out with many misspellings that are impossible to correct. Usually for an hour-long interview it takes me another hour to go through and fix mistakes, filling in gaps, and making guesses at uninterpretable words.

I would greatly benefit from a speech recognition solution that could create a fairly accurate transcript from audio, for example, live over the phone or from an mp3 file.

This need was emphasized to me even more this week, when I attended a conference and spent two days trying to take notes and capture useful quotes from speakers. I have a digital voice recorder and have all of the presentations in mp3 format, but it’s going to be quite a challenge to comb through all of that audio to find relevant quotes for the articles I will be writing about the conference. How much easier it would be it I had a software application that could convert all of those mp3s into fairly accurate text transcripts!

Unfortunately, it appears that voice recognition software is not ready to handle meetings and so on where multiple voices are involved. These systems have to be trained to recognized the voice of a single user.

I’m using this blog post to mark and share some possible solutions I have encountered. I will plan to add to this list as time goes — if and when the technology continues to improve.

+ Dragon Naturally Speaking by Nuance is supposed to be the best reasonably-priced speech recognition software for professional use. Nuance says Dragon is not able to transcribe multiple voices, but I’m tempted to shell out the $200 just to see what kind of results I might get with it. Suppose it were 50 percent accurate transcribing unfamiliar voices? That might be good enough for me.

+ Windows has its own built-in speech recognition capability. I plan to test this out to see whether I can make it work somehow. However, it’s hard to believe that Microsoft could come up with a better solution than a specialist company like Nuance.

+ One suggestion I’ve run into a lot is to transcribe a meeting or lecture by “parroting” or “re-speaking.” In other words, using speech rec software like Dragon, you listen to the recording of the meeting on headphones and repeat what you hear into your computer mic. Because Dragon is trained to your voice, it can create an automatic transcript. Sounds laborious, but it would probably be better that having to type it all out myself.

+ I also heard about a company called Koemei that has a cloud-based solution for converting video and audio assets into text. Looks as if this might work pretty well, however, their entry-level service is $149 per month. That sounds like a lot, but maybe someday…. For $20 per month I would definitely try it.

+ Another idea I have thought of is to call my Google Voice number and play the audio recording into my voicemail. Google Voice automatically transcribes my voicemails into text and often does an acceptable job — good enough so I could paste the results into a word processor and make quick corrections. I’m not sure yet if Google Voice can handle long audio streams, though. I’m thinking about testing this solution to see if I can make it work somehow.

+ Here’s an interesting video by Chaelaz showing how to use YouTube’s closed-captioning transcription service to convert audio to text. Looks as if you would have to create a video first and upload it to YouTube, but that’s an interesting possible work-around for what I’m trying to do.

ARB — 21 June 2013

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