shirley | shirley

The easiest way is to use pandas directly:

You can do it with the $event parameter. Make sure to compare your values safely.

If your value is not in the right type or has spaces or unwanted chars, this c.state == val might not work.

You can use the trim function to compare your value safely: c.state.trim() == val.trim()

HTML

According to the logs you provided, the voice of the user is not detected. The meanings of logs and status codes are as follows:

solution

1. It is recommended that you add logs to the callback method of the MLAsrListener listener to view the speech recognition process.

1. You are advised to check mSpeechRecognizer.destroy(). Check whether this method is invoked prematurely and has ended before it starts.

2. Check whether the device is faulty or whether the microphone of the device is invalid. Replace the device and perform the test.

After reviewing your logs, the following errors were found:

The reason for this error is:The Languagecode for speech recognition exceeds 10.

You can view the code here:

Ensure that the speech recognition Languagecode does not exceed 10.

11203 ,subError code: 3002,errorMessage: Service unavailable

The cause of this error is that the app_id information is not found in the project.

You are advised to check whether the agconnect-services.json file exists in the project, as shown in the following

If the file does not exist, you need to add it to the project. If the file exists, ensure that app_id is correct.

For details, see the following Docs.

1. Check whether Automatic Speech Recognition fails to be enabled.

   If Automatic Speech Recognition fails to be enabled, you can obtain the cause by using the onError(int error, String errorMessage) method of the MLAsrListener class, as shown in the following figure.

You can add the above method to the listener's class:

2.If speech recognition is enabled successfully but the speech recognition result is not obtained:

The MLAsrConstants.FEATURE parameter is set to FUNCTION_ALLINONE. Therefore, you need to obtain the speech recognition result in the onResults(Bundle results) method, as shown in the following figure.

The problem in your code is that the reduce function you pass to reduceByKey doesn't produce the same data type as the RDD values. The lambda function returns an int while your values are of type string.

To understand this simply consider how the reduce works. The function is applied to the first 2 values, then the result of the function is added to the third value, and so on...

Note that even the one that worked for you isn't actually correct. For example, it returns ('Danner, Blythe', 'Pear') instead of ('Danner, Blythe', 4).

You should first transform the values into their corresponding length then reduce by key :

You're looking for a map, not a reduceByKey. There is nothing to reduce, because your data is already grouped by key, so nothing is done on your RDD and you got back the original RDD.

The reason your second solution keeps writing the unfound name is because it searches each line of file2.txt looking for a match and adds to file3.txt each time.

What you can do instead is introduce a new variable to store the value you want to add to file3.txt and then outside of the loop is when you actually append that value to your file.

Here is a working example:

I have a turnaround solution, which works (not that pretty). You would turn your withStyles into a currying function, that takes keyframesProps, and at your key frame definition you would use an IIFE that returns the object with its properties:

Try something like this:

You can split string at each word and perform the operation.

In base R :