I am trying to use the IBM Watson speech to text API/service in the following Python program.
import json
import os
import sys
from watson_developer_cloud import SpeechToTextV1
def transcribe_audio(audio_file_name) :
IBM_USERNAME = "yourusername"
IBM_PASSWORD = "yourpassword"
#what changes should be made here instead of username and password
stt = SpeechToTextV1(username=IBM_USERNAME, password=IBM_PASSWORD)
audio_file = open(audio_file_name, "rb")
json_file = os.path.abspath("america")+".json";
with open(json_file, 'w') as fp:
result = stt.recognize(audio_file,timestamps=True,content_type='audio/wav', inactivity_timeout =-1,word_confidence = True)
result.get_result()
json.dump(result, fp, indent=2)
script = "Script is : "
for rows in result['results']:
script += rows['alternatives'][0]['transcript']
print(script)
transcribe_audio("america.wav")
This code gave me an authentication error as mentioned in the title because IBM changed the authorization method from username + password to apikey
very recently.
Could anybody tell me what changes should be made in this?
And also how to generate the apikey on IBM Watson speech to text with username and password?
I am new to speech recognition, please let me know. Thanks in advance.
All the information you want is in the API documentation, including how to obtain the API Key - https://cloud.ibm.com/apidocs/speech-to-text?code=python
Related
I'm calling a simple python function in google cloud but cannot get it to save. It shows this error:
"Function failed on loading user code. This is likely due to a bug in the user code. Error message: Error: please examine your function logs to see the error cause: https://cloud.google.com/functions/docs/monitoring/logging#viewing_logs. Additional troubleshooting documentation can be found at https://cloud.google.com/functions/docs/troubleshooting#logging. Please visit https://cloud.google.com/functions/docs/troubleshooting for in-depth troubleshooting documentation."
Logs don't seem to show much that would indicate error in the code. I followed this guide: https://blog.thereportapi.com/automate-a-daily-etl-of-currency-rates-into-bigquery/
With the only difference environment variables and the endpoint I'm using.
Code is below, which is just a get request followed by a push of data into a table.
import requests
import json
import time;
import os;
from google.cloud import bigquery
# Set any default values for these variables if they are not found from Environment variables
PROJECT_ID = os.environ.get("PROJECT_ID", "xxxxxxxxxxxxxx")
EXCHANGERATESAPI_KEY = os.environ.get("EXCHANGERATESAPI_KEY", "xxxxxxxxxxxxxxx")
REGIONAL_ENDPOINT = os.environ.get("REGIONAL_ENDPOINT", "europe-west1")
DATASET_ID = os.environ.get("DATASET_ID", "currency_rates")
TABLE_NAME = os.environ.get("TABLE_NAME", "currency_rates")
BASE_CURRENCY = os.environ.get("BASE_CURRENCY", "SEK")
SYMBOLS = os.environ.get("SYMBOLS", "NOK,EUR,USD,GBP")
def hello_world(request):
latest_response = get_latest_currency_rates();
write_to_bq(latest_response)
return "Success"
def get_latest_currency_rates():
PARAMS={'access_key': EXCHANGERATESAPI_KEY , 'symbols': SYMBOLS, 'base': BASE_CURRENCY}
response = requests.get("https://api.exchangeratesapi.io/v1/latest", params=PARAMS)
print(response.json())
return response.json()
def write_to_bq(response):
# Instantiates a client
bigquery_client = bigquery.Client(project=PROJECT_ID)
# Prepares a reference to the dataset
dataset_ref = bigquery_client.dataset(DATASET_ID)
table_ref = dataset_ref.table(TABLE_NAME)
table = bigquery_client.get_table(table_ref)
# get the current timestamp so we know how fresh the data is
timestamp = time.time()
jsondump = json.dumps(response) #Returns a string
# Ensure the Response is a String not JSON
rows_to_insert = [{"timestamp":timestamp,"data":jsondump}]
errors = bigquery_client.insert_rows(table, rows_to_insert) # API request
print(errors)
assert errors == []
I tried just the part that does the get request with an offline editor and I can confirm a response works fine. I suspect it might have to do something with permissions or the way the script tries to access the database.
I have this block of code that basically translates text from one language to another using the cloud translate API. The problem is that this code always throws the error: "Caller's project doesn't match parent project". What could be the problem?
translation_separator = "translated_text: "
language_separator = "detected_language_code: "
translate_client = translate.TranslationServiceClient()
# parent = translate_client.location_path(
# self.translate_project_id, self.translate_location
# )
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = (
os.getcwd()
+ "/translator_credentials.json"
)
# Text can also be a sequence of strings, in which case this method
# will return a sequence of results for each text.
try:
result = str(
translate_client.translate_text(
request={
"contents": [text],
"target_language_code": self.target_language_code,
"parent": f'projects/{self.translate_project_id}/'
f'locations/{self.translate_location}',
"model": self.translate_model
}
)
)
print(result)
except Exception as e:
print("error here>>>>>", e)
Your issue seems to be related to the authentication method that you are using on your application, please follow the guide for authention methods with the translate API. If you are trying to pass the credentials using code, you can explicitly point to your service account file in code with:
def explicit():
from google.cloud import storage
# Explicitly use service account credentials by specifying the private key
# file.
storage_client = storage.Client.from_service_account_json(
'service_account.json')
Also, there is a codelab for getting started with the translation API with Python, this is a great step by step getting started guide for running the translate API with Python.
If the issue persists, you can try creating a Public Issue Tracker for Google Support
Im using Python 3.8 and i copy pasted this code as a test.
from google.cloud import texttospeech
# Instantiates a client
client = texttospeech.TextToSpeechClient()
# Set the text input to be synthesized
synthesis_input = texttospeech.SynthesisInput(text="Hello, World!")
# Build the voice request, select the language code ("en-US") and the ssml
# voice gender ("neutral")
voice = texttospeech.VoiceSelectionParams(
language_code="en-US", ssml_gender=texttospeech.SsmlVoiceGender.NEUTRAL
)
# Select the type of audio file you want returned
audio_config = texttospeech.AudioConfig(
audio_encoding=texttospeech.AudioEncoding.MP3
)
# Perform the text-to-speech request on the text input with the selected
# voice parameters and audio file type
response = client.synthesize_speech(
input=synthesis_input, voice=voice, audio_config=audio_config
)
# The response's audio_content is binary.
with open("output.mp3", "wb") as out:
# Write the response to the output file.
out.write(response.audio_content)
print('Audio content written to file "output.mp3"')
This is the code that is shown by google as can be seen here : GOOGLE LINK
Now my problem is that i get this error
PS C:\Users\User\Desktop> & C:/Users/User/AppData/Local/Programs/Python/Python38/python.exe "c:/Users/User/Desktop/from google.cloud import texttospeech.py"
Traceback (most recent call last):
File "c:/Users/User/Desktop/from google.cloud import texttospeech.py", line 7, in <module>
synthesis_input = texttospeech.types.SynthesisInput(text="Hello, World!")
AttributeError: module 'google.cloud.texttospeech' has no attribute 'types'
PS C:\Users\User\Desktop>
I tried changeing this to add the credentials inside the code but the problem persists.
This is the line i changed:
client = texttospeech.TextToSpeechClient(credentials="VoiceAutomated-239f1c05600c.json")
I could solve this error by downgrading the library:
pip3 install "google-cloud-texttospeech<2.0.0"
I got the same error when running that script, i checked the source code and the interface has changed, basically you need to delete all "enums" and "types". It will look similar to this:
# Instantiates a client
client = texttospeech.TextToSpeechClient()
# Set the text input to be synthesized
synthesis_input = texttospeech.SynthesisInput(text="Hello, World!")
# Build the voice request, select the language code ("en-US") and the ssml
# voice gender ("neutral")
voice = texttospeech.VoiceSelectionParams(
language_code='en-US',
ssml_gender=texttospeech.SsmlVoiceGender.NEUTRAL)
# Select the type of audio file you want returned
audio_config = texttospeech.AudioConfig(
audio_encoding=texttospeech.AudioEncoding.MP3)
# Perform the text-to-speech request on the text input with the selected
# voice parameters and audio file type
response = client.synthesize_speech(input=synthesis_input, voice=voice, audio_config=audio_config)
# The response's audio_content is binary.
with open('output.mp3', 'wb') as out:
# Write the response to the output file.
out.write(response.audio_content)
print('Audio content written to file "output.mp3"')
I debug the code and to get it to work i had to write enums and types when needed. Taking the text to speech google documentation example and including some little adjusments:
"""Synthesizes speech from the input string of text or ssml.
Note: ssml must be well-formed according to:
https://www.w3.org/TR/speech-synthesis/
"""
from google.cloud import texttospeech
import os
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "./config/credentials.json"
# Instantiates a client
client = texttospeech.TextToSpeechClient()
# Set the text input to be synthesized
synthesis_input = texttospeech.types.SynthesisInput(text="Hello, World!")
# Build the voice request, select the language code ("en-US") and the ssml
# voice gender ("neutral")
voice = texttospeech.types.VoiceSelectionParams(
language_code="en-US", ssml_gender=texttospeech.enums.SsmlVoiceGender.NEUTRAL
)
# Select the type of audio file you want returned
audio_config = texttospeech.types.AudioConfig(
audio_encoding=texttospeech.enums.AudioEncoding.MP3
)
# Perform the text-to-speech request on the text input with the selected
# voice parameters and audio file type
response = client.synthesize_speech(
input_=synthesis_input, voice=voice, audio_config=audio_config
)
# The response's audio_content is binary.
with open("./output_tts/output.mp3", "wb") as out:
# Write the response to the output file.
out.write(response.audio_content)
print('Audio content written to file "output.mp3"')
hope this works for you
It will work Python 3.6 but it won't work with Python 3.7 with latest update of google-cloud-texttospeech. If you want us it with Python 3.7 Try the below code.
from google.cloud import texttospeech
def foo():
client = texttospeech.TextToSpeechClient(credentials=your_google_creds_here)
translated_text = Text
synthesis_input = texttospeech.types.SynthesisInput(text=translated_text)
pitch = 1
speaking_rate = 1
lang_code = 'en-us' # your_lang_code_hear
gender = 'male'
gender_data = {
'NEUTRAL': texttospeech.enums.SsmlVoiceGender.NEUTRAL,
'FEMALE': texttospeech.enums.SsmlVoiceGender.FEMALE,
'MALE': texttospeech.enums.SsmlVoiceGender.MALE
}
voice = texttospeech.types.VoiceSelectionParams(language_code=lang_code, ssml_gender=gender_data[gender.upper()])
audio_config = texttospeech.types.AudioConfig(
audio_encoding=texttospeech.enums.AudioEncoding.MP3, speaking_rate=float(speaking_rate), pitch=float(pitch)
)
print('Voice config and Audio config : ', voice, audio_config)
response = client.synthesize_speech(
synthesis_input, voice, audio_config)
You need to migrate to version 2.0 visit the site below for details on the changes you need to make since you most likely followed a tutorial using an older version of texttospeech:
https://googleapis.dev/python/texttospeech/2.0.0/UPGRADING.html
I will also include an example using the beta version of 2.0.0.
import google.cloud.texttospeech_v1beta1 as ts
import time
nm = "en-US-Wavenet-I"
hz = 48000
def useTextToSpeech(speaking, lang, speed,stinger):
client = ts.TextToSpeechClient()
synthesis_input = ts.SynthesisInput(text=speaking)
voice = ts.VoiceSelectionParams(
language_code=lang,
ssml_gender=ts.SsmlVoiceGender.MALE,
name=nm,
)
audio_config = ts.AudioConfig(
audio_encoding=ts.AudioEncoding.OGG_OPUS,
speaking_rate=speed,
pitch = 1.2,
sample_rate_hertz=hz,
effects_profile_id=['headphone-class-device' ],
)
response = client.synthesize_speech(
request={
"input": synthesis_input,
"voice":voice,
"audio_config":audio_config
}
)
with open((stinger+'.opus'), 'wb') as out:
out.write(response.audio_content)
print('Audio content written to file as "'+stinger+'.opus"')
from playsound import playsound
import os
#playsound(os.path.abspath((stinger+'.opus')))
output = str("Make sure when you follow tutorials they are using the most up to date version of the Api!")
useTextToSpeech(output, "en-US-Wavenet-I",1.0,("example"+str(1)))
I want to access some charts -which I have saved in Looker- within Databricks. Part of this process is the authentication. I have one Looker auth-script which works but only pulls the tabular results into Databricks which corresponds to a Looker-View. Instead, I want ONLY the charts to be accessed in Databricks which will correspond to a Looker-look or Looker-space. However, when I follow the tutorial on https://discourse.looker.com/t/generating-a-powerpoint-presentation-from-all-looks-in-a-space/8191, I am not able to authenticate with their script. Hopefully, someone can help.
**Working auth-script for Looker-Views**
import looker_tools as tools
api=tools.LookerApi(
api_endpoint="abcd",
client_id=dbutils.secrets.get(scope="looker-api", key="looker_client_id"),
client_secret=dbutils.secrets.get(scope="looker-api",key="looker_client_secret")
)
token = api.login()
**Desired auth-script for Looker-Space/Looks as per tutorial link**
looker_instance = 'your-company.looker.com'
target_space = # 'Period over Period' Space on the Looker instance
client_id = 'xxxxxxxx'
client_secret = 'xxxxxxxx'
# instantiate Auth API
unauthenticated_client = looker_client.ApiClient(configuration=None)
unauthenticated_client.configuration.host = f'https://{looker_instance}:19999/api/3.0/'
unauthenticated_authApi = looker_client.ApiAuthApi(unauthenticated_client)
# authenticate client
token = unauthenticated_authApi.login(client_id=client_id, client_secret=client_secret)
client = looker_client.ApiClient(header_name='Authorization', header_value='token ' + token.access_token)
client.configuration.host = f'https://{looker_instance}:19999/api/3.0/'
I tried translating the code from Current to DESIRED auth-script but the error states the looker_client is not defined!
looker_instance = 'abcd'
target_space = 123
client_id = dbutils.secrets.get(scope="looker-api", key="looker_client_id")
client_secret = dbutils.secrets.get(scope="looker-api",key="looker_client_secret")
# instantiate Auth API
unauthenticated_client = looker_client.ApiClient(configuration=None) --> This line fails!!
unauthenticated_client.configuration.host = f'https://{looker_instance}:19999/api/3.0/'
unauthenticated_authApi = looker_client.ApiAuthApi(unauthenticated_client)
# authenticate client
token = unauthenticated_authApi.login(client_id=client_id, client_secret=client_secret)
client = looker_client.ApiClient(header_name='Authorization', header_value='token ' + token.access_token)
client.configuration.host = f'https://{looker_instance}:19999/api/3.0/'
I hope someone can help on how to define looker_client properly. Thanks.
It looks like this one was resolved here: https://discourse.looker.com/t/generating-a-powerpoint-presentation-from-all-looks-in-a-space/8191/15?u=izzy for those following along at home. There's another issue, but the NameError: name ‘looker_client’ is not defined error was resolved by adding a necessary import:
import looker_client_30 as looker_client
i have found this interesting article here https://developer.byu.edu/docs/consume-api/use-api/oauth-20/oauth-20-python-sample-code
in this article there is an example how to call an oauth2 api using authorization_code flow. the problem with this approach is that you need to open a new browser, get the code and paste in the script. i would open and get the code directly from python script. is it possible?
print "go to the following url on the browser and enter the code from the
returned url: "
print "--- " + authorization_redirect_url + " ---"
access_token = raw_input('access_token: ')
I have been battling with this same problem today and found that the following worked for me. You'll need:
An API ID
A secret key
the access token url
I then used requests_oauthlib: https://github.com/requests/requests-oauthlib
from requests_oauthlib import OAuth2Session
# Both id and secret should be provided by whoever owns the api
myid = 'ID_Supplied'
my_secret = 'Secret_pass'
access_token_url = "https://example.com/connect/token" # suffix is also an example
client = BackendApplicationClient(client_id=myid)
oauth = OAuth2Session(client=client)
token = oauth.fetch_token(token_url=access_token_url, client_id=myid,
client_secret=my_secret)
print(token)