"cadence_regulatable_result": "completeRecognition","appserver_results": {"status": "success","final_response": 0,"payload": {"actions": [{"speaker": "user","type": "conversation","nbest_text": {"confidences": [478,0,0],"words": [[{"stime": 0,"etime": 1710,"word": "ConnectedDrive\\*no-space-before","confidence": "0.241"}],[{"stime": 0,"etime": 1020,"word": "Connected\\*no-space-before","confidence": "0.0"},{"stime": 1020,"etime": 1710,"word": "drive","confidence": "0.0"}],[{"stime": 0,"etime": 900,"word": "Connect\\*no-space-before","confidence": "0.0"},{"stime": 900,"etime": 980,"word": "to","confidence": "0.0"},{"stime": 980,"etime": 1710,"word": "drive","confidence": "0.0"}]],"transcriptions"= ["ConnectedDrive","Connected drive","Connect to drive"]}}]}},"final_response": 0,"prompt": "","result_format": "appserver_post_results"
}: form-data;name="QueryResult"Content-Type: application/JSON;charset=utf-8Nuance-Context: efb3d3ce-ef50-4e83-8c31-063c3f5208aa{"status_code": 0,"result_type": "DRAGON_NLU_ASR_CMD","NMAS_PRFX_SESSION_ID": "f786f0be-d547-4fca-8d72-96429a30c9db","NMAS_PRFX_TRANSACTION_ID": "1","audio_transfer_info": {"packages": [{"time": "20151221085512579","bytes": 1633},{"time": "20151221085512598","bytes": 3969}],"nss_server": "10.56.11.186:4503","end_time": "20151221085512596","audio_id": 1,"start_time": "20151221085512303"},"cadence_regulatable_result": "completeRecognition","appserver_results": {"status": "success","final_response": 1,"payload": {"diagnostic_info": {"adk_dialog_manager_status": "undefined","nlu_version": "[NLU_PROJECT:NVCCP-eng-USA];[D0160932];[VL-Models:Version: vl.1.100.12-2-GMT20151130160335]","nlps_host": "mt-dmz-nlps002.nuance.com:8636","nlps_ip": "10.56.10.51","application": "AUDI_2017","nlu_component_flow": "[Input:VoiceJSON] [FieldID|auto_main] [NLUlib|C-eckart-r$Rev$.f20151118.1250] [build|G-r72490M.f20151130.1055] [vlmodel|Version: 2-GMT20151130160335] [Flow|+VlingoTokenized]","third_party_delay": "0","nmaid": "AUDI_SDS_2017_EXT_20151203","nlps_profile": "AUDI_2017","fieldId": "auto_main","nlps_profile_package_version": "r159218","nlu_annotator": "com-GBR.ncs51.VlingoNLU-client-qNVCCP_NCS51","ext_map_time": "2","nlu_use_literal_annotator": "0","int_map_time": "2","nlps_nlu_type": "nlu_project","nlu_language": "eng-GBR","timing": {"finalRespSentDelay": "188","intermediateRespSentDelay": "648"},"nlps_profile_package": "AUDI_2017"},"actions": [{"Input": {"Interpretations": ["ConnectedDrive"],"Type": "asr"},"Instances": [{"nlu_classification": {"Domain": "UDE","Intention": "Unspecified"},"nlu_interpretation_index": 1,"nlu_slot_details": {"Name": {"literal": "ConnectedDrive"},"Search-phrase": {"literal": "connecteddrive"}},"interpretation_confidence": 4549}],"type": "nlu_results","api_version": "1.0"}],"nlps_version": "nlps(z):6.1.100.12.2-B359;Version: nlps-base-GMT20151130193521;"}},

Firstly, I am searching for transcriptions and interpretations word in the .txt file (So I am using regex) then I want to compare the FIRST value of transcriptions ("Drive me to a charging station") with the Interpreations value ("Drive me to a charging station"). If I give as below in my program, it is just printing as Recognition is INVALID

directory =os.path.join("C:\Users\hemanth_venkatappa\Desktop\Working\pcm-audio\English")
for subdir, dirs, files in os.walk(directory): for file in files:if file.endswith(".txt"): content=json.load(file)if "status_code" in content:if content["status_code"]==0:print("valid")

You can take a look at difflib for text comparison using Python.

The difflib module contains tools for computing and working withdifferences between sequences. It is especially useful for comparingtext, and includes functions that produce reports using several commondifference formats.

difflib tutorial

Using this module you can evaluate differences between two strings or .txt files this way:

import diffliba = ["Drive me to a charging station", "Drive me to charging station", "Drive me to a charging Station"]
correct = ["Drive me to a charging station"]print difflib.SequenceMatcher(None, a[0], correct[0]).ratio()
>> 1.0print difflib.SequenceMatcher(None, a[1], correct[0]).ratio()
>> 0.965517241379print difflib.SequenceMatcher(None, a[2], correct[0]).ratio()
>> 0.966666666667

As you can see, the .ratio() between a[0] and correct is 1.0 or 100%. This means they're the same string.

You can use a loop to evaluate the ratios and if ratio == 1.0 then print "Recognition is VALID "

Also if you don't wanna use the .ratio() between the strings, you can check the differences using:

d = difflib.Differ()
diff = d.compare(a, correct)
print '\n'.join(diff)

And this block of code gives me:

  Drive me to a charging          # no signal at the start means it's the same string
- Drive me to charging station    # this string has less chars than the expected string
- Drive me to a charging Station  # same here

Then you'll have to figure a way to print Recognition is VALID or INVALID according to your expectations.