Setting up a VM instance on Google Cloud
Setting up a VM instance on Google Cloud
Reserve an IP Address
Moving files off of VM
From local machine, copy a file from the machine cs231-vm
gcloud compute scp --recurse cs231-vm:/path/to/remote /path/to/local
The --recurse flag ensures allows one to copy directories and their contents
Entering/Exiting the VM from local terminal
If your virtual machine is called cs231-vm then turn on the virtual machine
gcloud compute instances start cs231-vm
Now SSH into the virtual machine
gcloud compute ssh --zone=us-west1-b cs231-vm
You can now start Python, run Jupyter. The interface should be local, but computations will occur on the cloud
Log out of the virtual machine
logout
After successfully logging out, shut down the instance (and stop billing)
gcloud compute instances stop cs231-vm
Fixing permissions to install packages
If installing or updating packages is persistently throwing a permissions error
cd ~
conda clean --all
sudo chown -R [username]:[username] /home/shared
Detaching sessions using GNU screen
SSH into the server, and then run
screen
Now start your process as you would normally. To detach it, hit [Ctrl]+A and then [Ctrl]+D. You can now log out of the server
To re-enter, SSH back into the server and then run
screen -r
If there are multiple living processes, you will be prompted to enter the process ID before resuming
Check to see what sessions are detached
screen -list
Kill any sessions without entering them
screen -X -S [process id] quit
More instructions here
Accessing multiple Google Cloud projects on the same local computer
Make a new project on the Google Cloud Console and then enable the appropriate API for the project
Check that the new project is alive by running locally
gcloud projects list
Can switch projects locally
gcloud config set project my-project
Can set a default using the variable $CLOUDSDK_CORE_PROJECT
Can check current setup using
gcloud config list
Running speech recognition
File needs to be in WAV or FLAC format already
ffmpeg -i input.mp3 -ac 1 output.flac
Or, for a video
ffmpeg -i input.mp4 -ac 1 output.flac
The -ac 1 flag ensures that there is only one audio channel, which is currently a requirement
For short snippets < 1 min long,
gcloud ml speech recognize 'audio_file.flac' --language-code='en-US'
For longer snippets,
gcloud ml speech recognize-long-running 'audio_file.flac' --language-code='en-US' --async
This will return a [process ID], retrieve the transcript using
gcloud ml speech operations wait [process ID]
Can also give it a flag containining common words
--hints=[HINTS,...]
A list of strings containing word and phrase "hints" so that the speech
recognition is more likely to recognize them. This can be used to
improve the accuracy for specific words and phrases, for example, if
specific commands are typically spoken by the user. This can also be
used to add additional words to the vocabulary of the recognizer. See
https://cloud.google.com/speech/limits#content.
–configuration, –account are other useful flags
curl -s -H “Content-Type: application/json”
-H “Authorization: Bearer “$(gcloud auth print-access-token)
https://speech.googleapis.com/v1p1beta1/speech:recognize \
Run speech recognition with slightly more customizability
Create a bucket to store your FLAC files here: https://console.cloud.google.com/storage/browser Upload the files via the web GUI
gs://my-bucket-name/my_file.flac
From the command line
gsutil cp my_file.flac gs://my-bucket-name
View a list of all buckets here
Now put your settings into a local file called my_config.json
{
"config": {
"encoding":"FLAC",
"languageCode": "en-US",
"enableAutomaticPunctuation": true
},
"audio": {
"uri":"gs://my-bucket-name/my_file.flac"
}
}
Now run on Google Cloud using curl
curl -s -H "Content-Type: application/json" -H "Authorization: Bearer "$(gcloud auth print-access-token) https://speech.googleapis.com/v1p1beta1/speech:recognize -d @my_config.json
Note the v1p1beta1 because, as of when this is being written, certain settings (like punctuation) are still in beta testing
Occasionally you need to re-authenticate
gcloud auth application-default login
More info from documentation here
Dump output into a text file:
curl -s -H "Content-Type: application/json" -H "Authorization: Bearer "$(gcloud auth print-access-token) https://speech.googleapis.com/v1p1beta1/speech:recognize -d @my_config.json > "mm.json"
{
"config": {
"encoding":"FLAC",
"languageCode": "en-US",
"enableAutomaticPunctuation": true,
"model": "command_and_search"
},
"audio": {
"uri":"gs://transcriptions-wg/output.flac"
}
}
For audio files longer than 1 minute, make a different config file
{
"config": {
"encoding":"FLAC",
"languageCode": "en-US",
"enableAutomaticPunctuation": true,
"model": "command_and_search",
"speechContexts" : {
"phrases":["Nernst","chemistry","Cu"]
}
},
"audio": {
"uri":"gs://transcriptions-wg/my_audio.flac"
}
}
And run using
curl -s -H "Content-Type: application/json" -H "Authorization: Bearer "$(gcloud auth print-access-token) https://speech.googleapis.com/v1/speech:longrunningrecognize -d @my_config.json
curl -X POST -H "Authorization: Bearer "$(gcloud auth application-default print-access-token) -H "Content-Type: application/json; charset=utf-8" -d @my_config.json "https://speech.googleapis.com/v1p1beta1/speech:longrunningrecognize"
This time, to get the output, need to use a GET request
curl -H "Authorization: Bearer "$(gcloud auth application-default print-access-token) -H "Content-Type: application json; charset=utf-8" "https://speech.googleapis.com/v1operations/your-operation-name" > "output.json"
Can parse the output JSON with the tool jq, which may be installed as
brew install jq
Now fetch and concatenate all of the output text using
cat output.json | jq '.response.results[].alternatives[0].transcript' > transcript.txt
More info on long audio files is here
Merge above into a bash script
Make a bucket called my_transcriptions, and then install ffmpeg, gcloud, and jq on your local machine
Script takes one argument: `video_file.mp4’
#!/bin/bash
ffmpeg -i $1 -ac 1 my_audio.flac
gsutil cp my_audio.flac gs://transcriptions-wg
jq '.audio.uri = "gs://transcriptions-wg/my_audio.flac"' template.json > "$tmp" && mv "$tmp" template.json
curl -X POST -H "Authorization: Bearer "$(gcloud auth application-default print-access-token) -H "Content-Type: application/json; charset=utf-8" -d @templa\
te.json "https://speech.googleapis.com/v1p1beta1/speech:longrunningrecognize"
The parsing script takes a process ID argument and gets the transcript. It then empties the bucket, to avoid incurring long-term storage fees
#!/bin/bash
curl -H "Authorization: Bearer "$(gcloud auth application-default print-access-token) -H "Content-Type: application json; charset=utf-8" "https://speech.go\
ogleapis.com/v1p1beta1/operations/"$1 > output_raw.json
cat output_raw.json | jq '.response.results[].alternatives[0].transcript' > my_transcript.txt
gsutil rm gs://bucket/my_audio.flac
Run this script on the video nernst2.mp4 using
bash run_transcription.sh nernst2.mp4
A process ID number should be given. After giving it some time to run, print the output using to “my_transcription.txt” using
bash parse_transcription.sh [process ID]
Will throw a null error if transcription is not done yet.