5 ms·

IBM Watson Tone Analyzer

46 points by mrestko 11y ago

ihsw 11y ago
Is there a way to 're-tone' a message, eg: making someone sound more aggressive? Seems like the logical progression, if not full outright automatic generation of messages.
- eggoa 11y ago
  I've found that playing back a recording at 90% speed can make speakers sound strangely hostile and sarcastic...
  - anigbrowl 11y ago
    Heh. Makes sense, as people tend to speed up their speech when they're nervous, and become nervous in response to deliberate speech modulation of the sort you describe. To the GP I'm sure you could 're-tone' many messages, but as presented here the results would likely be unsatisfactory. Doing so effectively would require second- and third-order analysis and now you're getting into Hard Problems.
muglug 11y ago
It doesn't deal with negation very well – the phrase "I have never had a sad day with you" is marked as negative because it contains the word "sad".
- joefkelley 11y ago
  I also noticed this, and it seems like a pretty big flaw. It analyzed one of my emails as very confident because it saw the words "clear" and "sure", but in context, they were used in the phrases "None of this is clear to me" and "I am not totally sure"
  - akkiraju 11y ago
    We are working on dealing with negation. Our next update will have this capability.
jboons 11y ago
My initial impression is it doesn't seem analyze groups of words very well. It will pick emotional words out of the middle of a sentence and apply the emotion to the whole text, when the context of the sentence changes the meaning of the word. Quick example, "I hate your guts and I hope you die." -- Hope is picked out and noted as cheerful.
- sp332 11y ago
  I think it's aimed at business communication. It picks out terms that might be taken the wrong way, instead of trying to rewrite your whole communication.
  - jsprogrammer 11y ago
    So that your layoff notice can be 100% 'agreeable'?
    - kristopolous 11y ago
      when I was doing my stab at this problem (see comment above), the contextual power structure was important. that's why I coupled my model with flow analysis on the mail server end to assign subordination relations between parties when possible. A general solution is OK for liaisons but that's about it. The IBM demo appears to be just positioning Watson as a general business concierge here and doesn't seem to be concerned with a true assist on what Gardener calls interpersonal intelligence. Being able to write concisely and well doesn't necessarily mean you can permeate communication walls. A valid computer solution, in brief, involves continuous kernel application during the authorship; how the user responds to the system is itself part of the analysis. This isn't just binary sentiment analysis of product reviews using an SVM - that's childs' play compared to this. Even with the best solution I came up with, it's still just culturally specific ... cultural to the geolocation of the persons and the heritage of the people, but also to the industry itself. Something that may show weakness in one industry may show wisdom in another, hostility in another, and humility in another. For instance, say you met someone with whom you had a serious romantic interest. Would you exchange business cards, and then arrange a 9am skype call the following tuesday? It's just all so contextual. This rabbit hole runs deep.
andrewtbham 11y ago
Looks like it's doing emotional classification. Seems more geared towards a single word approach versus strong contextual classification. The synonyms for acknowledge on their example are not very good. Here is a link to the demo to test it out yourself. http://tone-analyzer-demo.mybluemix.net/ http://tone-analyzer-demo.mybluemix.net/
LunaSea 11y ago
Saying: You are a retarded goat. Is apparently a positive sentence.
- multinglets 11y ago
  Take out the "a" and it is.
  - bawana 11y ago
    'you are a nice asshole wanker' is also marked as cheerful and agreeable. I guess it has no clue about sarcasm.
anigbrowl 11y ago
It's interesting and I will keep it bookmarked for occasional use, but the classification into emotional, social and writing tones seem very arbitrary. At least part of the problem is that it seems to be working on single words, most of which are weighted more toward one classification or another based on aggregate use rather than any real context. Tools like this rarely seem to do any analysis at the phrase level, even though phrases of two or three words often contribute significant substantive or structural context. This is odd considering that we already have techniques for identifying statistically improbable phrases as intermediate lexical units (often used for detecting plagiarism). Is anyone aware of work going on in this area? I'm quite interested in lexical analysis, but I'm wary of investing a lot of time just to reinvent the wheel.
- andrewtbham 11y ago
  Yeh there is a lot of work going on in this area... check out all these lectures and the papers they cite. http://cs224d.stanford.edu/syllabus.html http://cs224d.stanford.edu/syllabus.html There is a race to create a virtual assistant and do question answering.. the big players are IBM Watson, Apple w/ Siri, Google, Microsoft w/ cortana, facebook M, and Amazon Echo.
bpodgursky 11y ago
Not suggesting that watson is good enough as-is (or anytime soon), but the implications of a truly reliable polygraph machine would be huge.
mpdehaan2 11y ago
I kind of like it how the example on this page is helping someone make their email more harsh, when it's already using exclamation points and starting sentences with "but" and is already heeps of negative. "We can't blame the economy" is passive aggressive, but it gets coded as green. Not being passive aggressive is good, but perhaps writing the sample email in a way that makes people want to work for this person would be a good idea instead.
- zeidrich 11y ago
  I'm not sure what you mean "It gets coded as green". It doesn't consider an entire statement, it considers word choice. Similarly, it says that green means that it's placed in the "writing tone" evaluation category, in that it tries to determine whether the writing comes across as analytical, confident or tentative. More like instructions or analysis and less like judgment or conversation. It's better to look at the demo in a different way. I mean, if I put your post into the analyzer it tells me that it's impassioned, and of that it's not very cheerful. If I put mine in, it looks very matter of fact. It's more analytical and matter-of-fact. The two posts imply that kind of difference in tone, and it's pretty cool to see. It's got a way to go, but trying different examples is interesting.
  - mpdehaan2 11y ago
    I mean that they are building a tool and the primary example is showing a typical passive-aggressive business email and the user is trying to make it worse. This is a strange reason to write a tool, and perhaps symptomatic of the corporate culture that sought to produce it. Teaching people to be nicer would be more interesting, and it's clear it is not dwelling on the right elements since it neglects to detect the overall tone of the email as being problematic.
yakult 11y ago
I can see a more advanced version of this being deployed as part of automated admin packages for commenting sites such as reddit and HN. Any comments of sufficiently negative tone gets auto-downvote/hidden/flagged, etc. In fact I wouldn't be surprised if it's already part pf the internal tooling.
PaulHoule 11y ago
I think IBM really inspired people with Watson, but they have failed to productize it and now they are using "Watson" as a marketing label for any A.I. related technology at all -- be it something very good that they started work on years ago (Speech Recognition) or something really bad that they aquired like AlchemyAPI.
dynomight 11y ago
I found IBM Watson to be wonderfully competent at absolutely nothing.

46 points by mrestko 11y ago

ihsw 11y ago

Is there a way to 're-tone' a message, eg: making someone sound more aggressive? Seems like the logical progression, if not full outright automatic generation of messages.

eggoa 11y ago
I've found that playing back a recording at 90% speed can make speakers sound strangely hostile and sarcastic...
- anigbrowl 11y ago
  Heh. Makes sense, as people tend to speed up their speech when they're nervous, and become nervous in response to deliberate speech modulation of the sort you describe. To the GP I'm sure you could 're-tone' many messages, but as presented here the results would likely be unsatisfactory. Doing so effectively would require second- and third-order analysis and now you're getting into Hard Problems.

muglug 11y ago

It doesn't deal with negation very well – the phrase "I have never had a sad day with you" is marked as negative because it contains the word "sad".

joefkelley 11y ago
I also noticed this, and it seems like a pretty big flaw. It analyzed one of my emails as very confident because it saw the words "clear" and "sure", but in context, they were used in the phrases "None of this is clear to me" and "I am not totally sure"
- akkiraju 11y ago
  We are working on dealing with negation. Our next update will have this capability.

jboons 11y ago

My initial impression is it doesn't seem analyze groups of words very well. It will pick emotional words out of the middle of a sentence and apply the emotion to the whole text, when the context of the sentence changes the meaning of the word. Quick example, "I hate your guts and I hope you die." -- Hope is picked out and noted as cheerful.

sp332 11y ago
I think it's aimed at business communication. It picks out terms that might be taken the wrong way, instead of trying to rewrite your whole communication.
- jsprogrammer 11y ago
  So that your layoff notice can be 100% 'agreeable'?
  - kristopolous 11y ago
    when I was doing my stab at this problem (see comment above), the contextual power structure was important. that's why I coupled my model with flow analysis on the mail server end to assign subordination relations between parties when possible. A general solution is OK for liaisons but that's about it. The IBM demo appears to be just positioning Watson as a general business concierge here and doesn't seem to be concerned with a true assist on what Gardener calls interpersonal intelligence. Being able to write concisely and well doesn't necessarily mean you can permeate communication walls. A valid computer solution, in brief, involves continuous kernel application during the authorship; how the user responds to the system is itself part of the analysis. This isn't just binary sentiment analysis of product reviews using an SVM - that's childs' play compared to this. Even with the best solution I came up with, it's still just culturally specific ... cultural to the geolocation of the persons and the heritage of the people, but also to the industry itself. Something that may show weakness in one industry may show wisdom in another, hostility in another, and humility in another. For instance, say you met someone with whom you had a serious romantic interest. Would you exchange business cards, and then arrange a 9am skype call the following tuesday? It's just all so contextual. This rabbit hole runs deep.

andrewtbham 11y ago

Looks like it's doing emotional classification. Seems more geared towards a single word approach versus strong contextual classification. The synonyms for acknowledge on their example are not very good. Here is a link to the demo to test it out yourself. http://tone-analyzer-demo.mybluemix.net/ http://tone-analyzer-demo.mybluemix.net/

LunaSea 11y ago

Saying: You are a retarded goat. Is apparently a positive sentence.

multinglets 11y ago
Take out the "a" and it is.
- bawana 11y ago
  'you are a nice asshole wanker' is also marked as cheerful and agreeable. I guess it has no clue about sarcasm.

anigbrowl 11y ago

It's interesting and I will keep it bookmarked for occasional use, but the classification into emotional, social and writing tones seem very arbitrary. At least part of the problem is that it seems to be working on single words, most of which are weighted more toward one classification or another based on aggregate use rather than any real context. Tools like this rarely seem to do any analysis at the phrase level, even though phrases of two or three words often contribute significant substantive or structural context. This is odd considering that we already have techniques for identifying statistically improbable phrases as intermediate lexical units (often used for detecting plagiarism). Is anyone aware of work going on in this area? I'm quite interested in lexical analysis, but I'm wary of investing a lot of time just to reinvent the wheel.

andrewtbham 11y ago
Yeh there is a lot of work going on in this area... check out all these lectures and the papers they cite. http://cs224d.stanford.edu/syllabus.html http://cs224d.stanford.edu/syllabus.html There is a race to create a virtual assistant and do question answering.. the big players are IBM Watson, Apple w/ Siri, Google, Microsoft w/ cortana, facebook M, and Amazon Echo.

bpodgursky 11y ago

Not suggesting that watson is good enough as-is (or anytime soon), but the implications of a truly reliable polygraph machine would be huge.

mpdehaan2 11y ago

I kind of like it how the example on this page is helping someone make their email more harsh, when it's already using exclamation points and starting sentences with "but" and is already heeps of negative. "We can't blame the economy" is passive aggressive, but it gets coded as green. Not being passive aggressive is good, but perhaps writing the sample email in a way that makes people want to work for this person would be a good idea instead.

zeidrich 11y ago
I'm not sure what you mean "It gets coded as green". It doesn't consider an entire statement, it considers word choice. Similarly, it says that green means that it's placed in the "writing tone" evaluation category, in that it tries to determine whether the writing comes across as analytical, confident or tentative. More like instructions or analysis and less like judgment or conversation. It's better to look at the demo in a different way. I mean, if I put your post into the analyzer it tells me that it's impassioned, and of that it's not very cheerful. If I put mine in, it looks very matter of fact. It's more analytical and matter-of-fact. The two posts imply that kind of difference in tone, and it's pretty cool to see. It's got a way to go, but trying different examples is interesting.
- mpdehaan2 11y ago
  I mean that they are building a tool and the primary example is showing a typical passive-aggressive business email and the user is trying to make it worse. This is a strange reason to write a tool, and perhaps symptomatic of the corporate culture that sought to produce it. Teaching people to be nicer would be more interesting, and it's clear it is not dwelling on the right elements since it neglects to detect the overall tone of the email as being problematic.

yakult 11y ago

I can see a more advanced version of this being deployed as part of automated admin packages for commenting sites such as reddit and HN. Any comments of sufficiently negative tone gets auto-downvote/hidden/flagged, etc. In fact I wouldn't be surprised if it's already part pf the internal tooling.

PaulHoule 11y ago

I think IBM really inspired people with Watson, but they have failed to productize it and now they are using "Watson" as a marketing label for any A.I. related technology at all -- be it something very good that they started work on years ago (Speech Recognition) or something really bad that they aquired like AlchemyAPI.

dynomight 11y ago

I found IBM Watson to be wonderfully competent at absolutely nothing.