As I said already sorry for the title. I have never worked with Azure API and have no idea what is wrong with the code, as I just copied from the documentation and put in my information.
Here is the code:
from azure.cognitiveservices.speech import AudioDataStream, SpeechConfig, SpeechSynthesizer, SpeechSynthesisOutputFormat
from azure.cognitiveservices.speech.audio import AudioOutputConfig
speech_config = SpeechConfig(subscription="ImagineHereAreNumbers", region="westeurope")
speech_config.speech_synthesis_language = "en-US"
speech_config.speech_synthesis_voice_name = "ChristopherNeural"
audio_config = AudioOutputConfig(filename=r'C:\Users\TheD4\OneDrive\Desktop\SpeechFolder\Azure.wav')
synthesizer = SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config)
synthesizer.speak_text_async("A simple test to write to a file.")
Well as I run this I get no error and in fact, get in my desired folder a .wav file, but this file has 0 bytes and it looks corrupted.
Now here is why I have no idea of what's wrong because if I remove this
speech_config.speech_synthesis_language = "en-US"
speech_config.speech_synthesis_voice_name = "ChristopherNeural"
So it becomes this
from azure.cognitiveservices.speech import AudioDataStream, SpeechConfig, SpeechSynthesizer, SpeechSynthesisOutputFormat
from azure.cognitiveservices.speech.audio import AudioOutputConfig
speech_config = SpeechConfig(subscription="ImagineHereAreNumbers", region="westeurope")
audio_config = AudioOutputConfig(filename=r'C:\Users\TheD4\OneDrive\Desktop\SpeechFolder\Azure.wav')
synthesizer = SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config)
synthesizer.speak_text_async("A simple test to write to a file.")
It now works all of the sudden, but with what I assume to be the basic/common voice.
So here is my question: how do I choose a voice that I want(btw is this one "en-US-JennyNeural" style="customerservice" or something among these lines)
Thank You in advance!
ChristopherNeural is not a valid voice name. The actual name of the voice is en-US-ChristopherNeural.
speech_config.speech_synthesis_voice_name = "en-US-ChristopherNeural"
This is well-documented on the Language support page of the Speech services documentation.
For other, more fine-grained control over voice characteristics, you'll require the use of SSML as outlined in text-to-speech-basics.py.
Related
I'm trying to adjust the pitch of IBM Watson but I can't seem to find any documentation on this whatsoever.
If you visit this link then you can see that there is an option to adjust the pitch/speed.
The code I have is very simply this:
from ibm_watson import TextToSpeechV1
from ibm_cloud_sdk_core.authenticators import IAMAuthenticator
authenticator = IAMAuthenticator('api_key')
text_to_speech = TextToSpeechV1(
authenticator=authenticator
)
text_to_speech.set_service_url('service_url')
sample = "insert what you want to say here"
with open('test.wav', 'wb') as audio_file:
audio_file.write(
text_to_speech.synthesize(
sample,
voice='en-GB_JamesV3Voice',
accept='audio/wav'
).get_result().content)
I have literally no idea what parameters to adjust in order to make the voice low. Thank you so much!
What you are looking for is the prosody element. Neural voices (V3) only use the pitch and rate attribute.
Using your example:
sample = 'Here is a <prosody pitch="150Hz"> modified pitch </prosody> example.'
sample = 'Here is a <prosody rate="x-slow"> modified rate </prosody> example.'
And here is a link to the docs about the prosody element:
https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-elements#prosody_element
I'm facing the following error while trying to persist log files to Azure Blob storage from Azure Batch execution - "FileUploadMiscError - A miscellaneous error was encountered while uploading one of the output files". This error doesn't give a lot of information as to what might be going wrong. I tried checking the Microsoft Documentation for this error code, but it doesn't mention this particular error code.
Below is the relevant code for adding the task to Azure Batch that I have ported from C# to Python for persisting the log files.
Note: The container that I have configured gets created when the task is added, but there's no blob inside.
import datetime
import logging
import os
import azure.storage.blob.models as blob_model
import yaml
from azure.batch import models
from azure.storage.blob.baseblobservice import BaseBlobService
from azure.storage.common.cloudstorageaccount import CloudStorageAccount
from dotenv import load_dotenv
LOG = logging.getLogger(__name__)
def add_tasks(batch_client, job_id, task_id, io_details, blob_details):
task_commands = "This is a placeholder. Actual code has an actual task. This gets completed successfully."
LOG.info("Configuring the blob storage details")
base_blob_service = BaseBlobService(
account_name=blob_details['account_name'],
account_key=blob_details['account_key'])
LOG.info("Base blob service created")
base_blob_service.create_container(
container_name=blob_details['container_name'], fail_on_exist=False)
LOG.info("Container present")
container_sas = base_blob_service.generate_container_shared_access_signature(
container_name=blob_details['container_name'],
permission=blob_model.ContainerPermissions(write=True),
expiry=datetime.datetime.now() + datetime.timedelta(days=1))
LOG.info(f"Container SAS created: {container_sas}")
container_url = base_blob_service.make_container_url(
container_name=blob_details['container_name'], sas_token=container_sas)
LOG.info(f"Container URL created: {container_url}")
# fpath = task_id + '/output.txt'
fpath = task_id
LOG.info(f"Creating output file object:")
out_files_list = list()
out_files = models.OutputFile(
file_pattern=r"../stderr.txt",
destination=models.OutputFileDestination(
container=models.OutputFileBlobContainerDestination(
container_url=container_url, path=fpath)),
upload_options=models.OutputFileUploadOptions(
upload_condition=models.OutputFileUploadCondition.task_completion))
out_files_list.append(out_files)
LOG.info(f"Output files: {out_files_list}")
LOG.info(f"Creating the task now: {task_id}")
task = models.TaskAddParameter(
id=task_id, command_line=task_commands, output_files=out_files_list)
batch_client.task.add(job_id=job_id, task=task)
LOG.info(f"Added task: {task_id}")
There is a bug in Batch's OutputFile handling which causes it to fail to upload to containers if the full container URL includes any query-string parameters other than the ones included in the SAS token. Unfortunately, the azure-storage-blob Python module includes an extra query string parameter when generating the URL via make_container_url.
This issue was just raised to us, and a fix will be released in the coming weeks, but an easy workaround is instead of using make_container_url to craft the URL, craft it yourself like so: container_url = 'https://{}/{}?{}'.format(blob_service.primary_endpoint, blob_details['container_name'], container_sas).
The resulting URL should look something like this: https://<account>.blob.core.windows.net/<container>?se=2019-01-12T01%3A34%3A05Z&sp=w&sv=2018-03-28&sr=c&sig=<sig> - specifically it shouldn't have restype=container in it (which is what the azure-storage-blob package is including)
I am trying to read mp3/wav data from google cloud and trying to implement audio diarization technique. Issue is that I am not able to read the result which has passed by google api in variable response.
below is my python code
speech_file = r'gs://pp003231/a4a.wav'
config = speech.types.RecognitionConfig(
encoding=speech.enums.RecognitionConfig.AudioEncoding.LINEAR16,
language_code='en-US',
enable_speaker_diarization=True,
diarization_speaker_count=2)
audio = speech.types.RecognitionAudio(uri=speech_file)
response = client.long_running_recognize(config, audio)
print response
result = response.results[-1]
print result
Output displayed on console is
Traceback (most recent call last):
File "a1.py", line 131, in
print response.results
AttributeError: 'Operation' object has no attribute 'results'
Can you please share your expert advice about what I am doing wrong?
Thanks for your help.
Its too late for the author of this thread. However, posting the solution for someone in future as I too had similar issue.
Change
result = response.results[-1]
to
result = response.result().results[-1]
and it will work fine
Do you have access to the wav file in your bucket? also, this is the entire code? It seems that the sample_rate_hertz and the imports are missing. Here you have the code copy/pasted from the google docs samples, but I edited it to have just the diarization function.
#!/usr/bin/env python
"""Google Cloud Speech API sample that demonstrates enhanced models
and recognition metadata.
Example usage:
python diarization.py
"""
import argparse
import io
def transcribe_file_with_diarization():
"""Transcribe the given audio file synchronously with diarization."""
# [START speech_transcribe_diarization_beta]
from google.cloud import speech_v1p1beta1 as speech
client = speech.SpeechClient()
audio = speech.types.RecognitionAudio(uri="gs://<YOUR_BUCKET/<YOUR_WAV_FILE>")
config = speech.types.RecognitionConfig(
encoding=speech.enums.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=8000,
language_code='en-US',
enable_speaker_diarization=True,
diarization_speaker_count=2)
print('Waiting for operation to complete...')
response = client.recognize(config, audio)
# The transcript within each result is separate and sequential per result.
# However, the words list within an alternative includes all the words
# from all the results thus far. Thus, to get all the words with speaker
# tags, you only have to take the words list from the last result:
result = response.results[-1]
words_info = result.alternatives[0].words
# Printing out the output:
for word_info in words_info:
print("word: '{}', speaker_tag: {}".format(word_info.word,
word_info.speaker_tag))
# [END speech_transcribe_diarization_beta]
if __name__ == '__main__':
transcribe_file_with_diarization()
To run the code just name it diarization.py and use the command:
python diarization.py
Also, you have to install the latest google-cloud-speech library:
pip install --upgrade google-cloud-speech
And you need to have the credentials of your service account in a json file, you can check more info here
OK, I have been trying to think of a solution/find a solution myself for quite some time but everything I am attempting either ends up not a solution, or too complex for me to attempt without knowing it will work.
I have a discord bot, made in python. The bots purpose is to parse a blog for HTML links, when a new HTML link is posted, it will the post the link into discord.
I am using a textfile to save the latest link, and then parsing the website every 30seconds to check if a new link has been posted by comparing the link at position 0 in the array to the link in the textfile.
Now, I have managed to host my bot on Heroku with some success however I have since learned that Heroku cannot modify my textfile since it pulls the code from github, any changes are reverted after ~24hours.
Since learning this I have attempted to host the textfile on an AWS S3 bucket, however I have now learned that it can add and delete files, but not modify existing ones, and can only write new files from existing files on my system, meaning if I could do this, I wouldn't need to do this since I would be able to modify the file actually on my system and not need to host it anywhere.
I am looking for hopefully simple solutions/suggestions.
I am open to changing the hosting/whatever is needed, however I cannot pay for hosting.
Thanks in advance.
EDIT
So, I am editing this because I have a working solution thanks to a suggestion commented below.
The solution is to get my python bot to commit the new file to github, and then use that commited file's content as the reference.
import base64
import os
from github import Github
from github import InputGitTreeElement
user = os.environ.get("GITHUB_USER")
password = os.environ.get("GITHUB_PASSWORD")
g = Github(user,password)
repo = g.get_user().get_repo('YOUR REPO NAME HERE')
file_list = [
'last_update.txt'
]
file_names = [
'last_update.txt',
]
def git_commit():
commit_message = 'News link update'
master_ref = repo.get_git_ref('heads/master')
master_sha = master_ref.object.sha
base_tree = repo.get_git_tree(master_sha)
element_list = list()
for i, entry in enumerate(file_list):
with open(entry) as input_file:
data = input_file.read()
if entry.endswith('.png'):
data = base64.b64encode(data)
element = InputGitTreeElement(file_names[i], '100644', 'blob', data)
element_list.append(element)
tree = repo.create_git_tree(element_list, base_tree)
parent = repo.get_git_commit(master_sha)
commit = repo.create_git_commit(commit_message, tree, [parent])
master_ref.edit(commit.sha)
I then have a method called 'check_latest_link' which checks my github repo's RAW format, and parses that HTML to source the contents and then assigns that content as a string to my variable 'last_saved_link'
import requests
def check_latest_link():
res = requests.get('[YOUR GITHUB PAGE LINK - RAW FORMAT]')
content = res.text
return(content)
Then in my main method I have the follow :
#client.event
async def task():
await client.wait_until_ready()
print('Running')
while True:
channel = discord.Object(id=channel_id)
#parse_links() is a method to parse HTML links from a website
news_links = parse_links()
last_saved_link = check_latest_link()
print('Running')
await asyncio.sleep(5)
#below compares the parsed HTML, to the saved reference,
#if they are not the same then there is a new link to post.
if last_saved_link != news_links[0]:
#the 3 methods below (read_file, delete_contents and save_to_file)
#are methods that simply do what they suggest to a text file specified elsewhere
read_file()
delete_contents()
save_to_file(news_links[0])
#then we have the git_commit previously shown.
git_commit()
#after git_commit, I was having an issue with the github reference
#not updating for a few minutes, so the bot posts the message and
#then goes to sleep for 500 seconds, this stops the bot from
#posting duplicate messages. because this is an async function,
#it will not stop other async functions from executing.
await client.send_message(channel, news_links[0])
await asyncio.sleep(500)
I am posting this so I can close the thread with an "Answer" - please refer to post edit.
I have searched the web far and wide for a still working example of uploading a photo to facebook through the Python API (Python for Facebook). Questions like this have been asked on stackoverflow before but non of the answers I have found work anymore.
What I got working is:
import facebook as fb
cfg = {
"page_id" : "my_page_id",
"access_token" : "my_access_token"
}
api = get_api(cfg)
msg = "Hello world!"
status = api.put_wall_post(msg)
where I have defined the get_api(cfg) function as this
graph = fb.GraphAPI(cfg['access_token'], version='2.2')
# Get page token to post as the page. You can skip
# the following if you want to post as yourself.
resp = graph.get_object('me/accounts')
page_access_token = None
for page in resp['data']:
if page['id'] == cfg['page_id']:
page_access_token = page['access_token']
graph = fb.GraphAPI(page_access_token)
return graph
And this does indeed post a message to my page.
However, if I instead want to upload an image everything goes wrong.
# Upload a profile photo for a Page.
api.put_photo(image=open("path_to/my_image.jpg",'rb').read(), message='Here's my image')
I get the dreaded GraphAPIError: (#324) Requires upload file for which non of the solutions on stackoverflow works for me.
If I instead issue the following command
api.put_photo(image=open("path_to/my_image.jpg",'rb').read(), album_path=cfg['page_id'] + "/picture")
I get GraphAPIError: (#1) Could not fetch picture for which I haven't been able to find a solution either.
Could someone out there please point me in the right direction of provide me with a currently working example? It would be greatly appreciated, thanks !
A 324 Facebook error can result from a few things depending on how the photo upload call was made
a missing image
an image not recognised by Facebook
incorrect directory path reference
A raw cURL call looks like
curl -F 'source=#my_image.jpg' 'https://graph.facebook.com/me/photos?access_token=YOUR_TOKEN'
As long as the above calls works, you can be sure the photo agrees with Facebook servers.
An example of how a 324 error can occur
touch meow.jpg
curl -F 'source=#meow.jpg' 'https://graph.facebook.com/me/photos?access_token=YOUR_TOKEN'
This can also occur for corrupted image files as you have seen.
Using .read() will dump the actual data
Empty File
>>> image=open("meow.jpg",'rb').read()
>>> image
''
Image File
>>> image=open("how.png",'rb').read()
>>> image
'\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00...
Both of these will not work with the call api.put_photo as you have seen and Klaus D. mentioned the call should be without read()
So this call
api.put_photo(image=open("path_to/my_image.jpg",'rb').read(), message='Here's my image')
actually becomes
api.put_photo('\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00...', message='Here's my image')
Which is just a string, which isn't what is wanted.
One needs the image reference <open file 'how.png', mode 'rb' at 0x1085b2390>
I know this is old and doesn't answer the question with the specified API, however, I came upon this via a search and hopefully my solution will help travelers on a similar path.
Using requests and tempfile
A quick example of how I do it using the tempfile and requests modules.
Download an image and upload to Facebook
The script below should grab an image from a given url, save it to a file within a temporary directory and automatically cleanup after finished.
In addition, I can confirm this works running on a Flask service on Google Cloud Run. That comes with the container runtime contract so that we can store the file in-memory.
import tempfile
import requests
# setup stuff - certainly change this
filename = "your-desired-filename"
filepath = f"{directory}/{filename}"
image_url = "your-image-url"
act_id = "your account id"
access_token = "your access token"
# create the temporary directory
temp_dir = tempfile.TemporaryDirectory()
directory = temp_dir.name
# stream the image bytes
res = requests.get(image_url, stream=True)
# write them to your filename at your temporary directory
# assuming this works
# add logic for non 200 status codes
with open(filepath, "wb+") as f:
f.write(res.content)
# prep the payload for the facebook call
files = {
"filename": open(filepath, "rb"),
}
url = f"https://graph.facebook.com/v10.0/{act_id}/adimages?access_token={access_token}"
# send the POST request
res = requests.post(url, files=files)
res.raise_for_status()
if res.status_code == 200:
# get your image data back
image_upload_data = res.json()
temp_dir.cleanup()
if "images" in image_upload_data:
return image_upload_data["images"][filepath.split("/")[-1]]
return image_upload_data
temp_dir.cleanup() # paranoid: just in case an error isn't raised