kandi X-RAY | utterances Summary
kandi X-RAY | utterances Summary
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Trending Discussions on utterances
Do we need to re-certify a deployed skill if we edit Entities (eg: add synonyms) to Dialogflow or edit Types in case of using Actions Builder?
Essentially is there an "Update Live Skill" option similar to Alexa Skills Kit, where any published skill can be updated immediately when changes are limited to sample utterances within an intent or slot/entity values....
ANSWERAnswered 2021-Jun-09 at 17:02
Yes updates to the conversational model will require a redeploy, which will require a review if you go to the beta or production channels. Alpha releases do not require a review.
The releases documentation may provide more information.
all. I am working on a personal NLP/NLU project using the nps_chat corpus. I am working on identifying all the questions asked and then doing some further analysis.
It is a rather large data set and is formatted as such:...
ANSWERAnswered 2021-Jun-04 at 21:30
Perhaps this is what you are looking for?
NOTE: An update/new question on this begins at =====================
Original post: I am working with utterances, statements spoken by children. From each utterance, if one or more words in the statement match a predefined list of multiple 'core' words (probably 300 words), then I want to input '1' into 'Core' (and if none, then input '0' into 'Core').
If there are one or more words in the statement that are NOT core words, then I want to input '1' into 'Fringe' (and if there are only core words and nothing extra, then input '0' into 'Fringe').
Basically, right now I have only the utterances and from those, I need to identify if any words match one of the core and if there are any extra words, identify those as fringe. Here is a snippet of my data....
ANSWERAnswered 2021-May-15 at 18:01
A little trick to do this is to replace (
gsub()) all core words in the utterances with an empty string
"". Then check if the length of the string (
nchar()) is still bigger than zero. If is bigger than zero it means that there are non-core words in the utterance. By applying
trimws() to the strings after replacing the core words we make sure that no unwanted whitespaces remain that would be counted as characters.
This is the code by itself.
We are developing a skill and my invocation name is "call onstar"
I got an intent "CallOnStarIntent"
I got the next utterances
"switch to onstar",
"access onstar emergency",
"access onstar advisor",
"connect to onstar emergency",
"connect to onstar advisor",
"connect to onstar",
"i want to use onstar",
"call onstar emergency",
"call onstar advisor",
These are the listed utterances and they are working fine when i try a utterance "call square" i get Amazon.FallBackIntent as expected. But when i tried with utterances like "ping onstar" , "play onstar", or any utterances that has the word onstar it returns CallOnStarIntent.
Does any one know why is this happening?
Thanks in advance....
ANSWERAnswered 2021-May-18 at 08:47
The list of utterances for an intent are not to be seen as a closed set of values like an enumeration in programming languages. They are only samples used to train your Alexa skill. It's described in the documentation page about best practices for sample utterances:
"Alexa also attempts to generalize based on the samples you provide to interpret spoken phrases that differ in minor ways from the samples specified."
I am working with a large JSON file specifically the persona dataset (download here)
Each entry in Persona-Chat is a dict with two keys personality and utterances, and the dataset is a list of entries....
ANSWERAnswered 2021-May-20 at 19:22
To fully flatten that file, you'd need something like
We have a solution hosted on a server which uses Dialog Flow to convert our utterances to intent. Example utterances: What are the activities for today, What are the activities for tomorrow, What is for lunch today. What is for lunch tomorrow.
We use entity: @sys.date-time for today/tomorrow. In response to these Dialog Flow sends us a date and time in this format (date, noon and time zone): "2021-05-18T12:00:00+06:00" (+6 seems to be India IST TZ).
A person can request these queries from anywhere in the world, hence today and tomorrow is relative to where the person is residing. We do know the TZ of the person requesting the service.
We use the Dialog flow's date, time and TZ and the TZ of the user and calculate the users date. The date comes our incorrect. Reason being that Dialog is always returning Time T12:00:00. If DF gave current time + TZ, our calculations would be correct.
How do we have Dialog Flow return actual time and not noon for Today/Tomorrow, so we can calculate the correct date for the user (using user's TZ - Time Zone)....
ANSWERAnswered 2021-May-18 at 18:00
You can pass an IANA time zone identifier such as
Asia/Kolkata in the
timeZone value in the query parameter, or set a default in the agent settings.
From the DialogFlow ES documentation:
The time zone of this conversational query from the time zone database, e.g., America/New_York, Europe/Paris. If not provided, the time zone specified in agent settings is used.
Also, India's time zone uses a
+05:30 offset. If you're seeing
+06:00, that could be any of 10 different time zones, but it's not India.
I am working with utterances, statements spoken by children. From each utterance, if one or more words in the statement match a predefined list of multiple 'core' words (probably 300 words), then I want to input '1' into 'Core' (and if none, then input '0' into 'Core').
Likewise, if there are one or more words in the statement that match a different predefined listed of 'fringe' words (probably 300 fringe words; again which are different than the core words), then I want to input '1' into 'Fringe' (and if none, then input '0' into 'Fringe').
Basically, right now I have only the utterances and from those, I need to identify if any words match one of the core and match any fringe word. Here is a snippet of my data....
ANSWERAnswered 2021-Apr-29 at 19:05
Here is a quick way to maybe solve your question (though I'm sure there are more elegant solutions)...
I have a large dataframe with utterances of variable
ANSWERAnswered 2021-May-06 at 11:37
You can subset
df by using the row (
seq_len(nrow(df)) and the value in
df$size, make a
table and calculate the
I have a (very large) dataframe with
words in utterances of different
sizes and corpus
frequencies of the words:
ANSWERAnswered 2021-May-06 at 06:49
I had to guess a lot but I think you are looking for this:
Here is part of the txt file I'm working with:...
ANSWERAnswered 2021-May-04 at 06:16
You were very close but this is how you would do it using regex:
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