Categories
Linux Raspberry Pi

Interpreting speech with a Raspberry Pi

Or the beginning or creating your own smart speaker

Intro

Imagine you could use a low-cost device to interpret speech without the aid of the big cloud services and their complexity and security and big-brotherly-ness. Well if you have a DIY mindset, you can!

I wanted to control the raspberry pi-based slideshow I have written about many times in the past with voice commands. The question became How could I do it and is it even possible at all? And would I need to master the complex apis provided by either Amazon or Google cloud services? Well, it turns out that it is possible to do passable speech to text without any external cloud provider; and I am very excited to share what I’ve learned so far.

Equipment

raspberry pi 4 (even my old RPI 3 seems to work)

USB microphone

Raspberry Pi OS

Skills

basic linux and python skills are required

vosk – your main tool

I’m going to cut to the chase and just tell you that the vosk api is how I got this all working, but not before I drove into several dead-ends.

Here are the vosk installation instructions, which do work on RPi:

Vosk Installation (alphacephei.com)

It will be helpful to install and test the examples:

git clone https://github.com/alphacep/vosk-api
cd vosk-api/python/example
python3 ./test_simple.py test.wav

On my RPi 4 it took 36 s the first time, and 6.6 s the second time to run this test.wav. So I got worried and fully expected it would be just too slow on these underpowed RPi systems.

But I forged ahead and looked for an example which could do real-time speech-to-text. They provide a microphone example. It requires some additional packages. But even after installing them it still produced a nasty segmentation fault. So I gave up on that. Then I noticed an ffmpeg-based example. Well, turns out I have lots of prior ffmpeg experience as I also post about live recording of audio with the raspberry pi.

It turns out their example was simply to use ffmpeg to interpret a file, but I didn’t know that to begin with. But I know my way around ffmpeg that I could use it for processing a lvie stream. So I made those changes, and voila. I’m glad to say I was dead wrong about the processing speed. On the RPi 4 it can keep up with its text-to-speech task in real time!

Basic program to examine your speech in real time

I developed the following python script based off one of the python examples from the api. I call it drjtst4.py, just to give it a name:

                    

#!/usr/bin/env python3

import subprocess
import re
from modules import aux_modules

from vosk import Model, KaldiRecognizer, SetLogLevel

SAMPLE_RATE = 16000

SetLogLevel(0)

model = Model(lang="en-us")
rec = KaldiRecognizer(model, SAMPLE_RATE)
start,start_a = 0,0
input_device = 'plughw:1,0'
phrase = ''
accumulating = False
# wake word hey photo is often confused with a photo by vosk...
wake_word_re = '^(hey|a) photo'

with subprocess.Popen(["ffmpeg","-loglevel", "quiet","-f","alsa","-i",
                            input_device,
                            "-ar", str(SAMPLE_RATE) , "-ac", "1", "-f", "s16le", "-"],
                            stdout=subprocess.PIPE) as process:

    while True:
        data = process.stdout.read(4000)
        if len(data) == 0:
            break
        if rec.AcceptWaveform(data):
            print('in first part')
            print(rec.Result())
            text = rec.PartialResult()
# text is a "string" which is basically a dict
            start,start_a,accumulating,phrase = aux_modules.process_text(wake_word_re,text,start,start_a,accumulating,phrase)
        else:
# this part always seems to be executed for whatever reason
            print('in else part')
            text = rec.PartialResult()
            start,start_a,accumulating,phrase = aux_modules.process_text(wake_word_re,text,start,start_a,accumulating,phrase)
            print(rec.PartialResult())

# we never seem to get here
    print(rec.FinalResult())
    print('In final part')
    text = rec.FinalResult()

I created a modules directory and in it a file called aux_modules.py. It look like this:

                    

import re,time,json

def process_text(wake_word_re,text_s,start,start_a,accumulating,phrase):
    max = 5.5 # seconds
    inactivity = 10 # seconds
    short_max = 1.5 # seconds
    elapsed = 0
    if time.time() - start_a < inactivity:
# Allow some time to elapse since we just took an action
        return start,start_a,accumulating,phrase
# convert text to real text. Real text is in 'partial'
    text_d = json.loads(text_s)
    text = ''
    if 'partial' in text_d:
        text = text_d['partial']
    if 'text' in text_d:
        text = text_d['text']
    if not text == '': phrase = text
    if re.search(wake_word_re,text):
        if not accumulating:
            start = time.time()
            accumulating = True
            print('Wake word detected. Now accumulating text.')
    l = len(re.split(r'\s',text))
    print('text, word ct',text,l)
    if accumulating:
        elapsed = time.time() - start
        print('Elapsed time:',elapsed)
        if l > 1:
           phrase = text
    if elapsed > max or (elapsed > short_max and l == 1):
# we're at a natural ending here...
        print('This is the total text',phrase)
# do some action
# reset everything
        accumulating = False
        phrase = ''
        start_a = time.time()
    return start,start_a,accumulating,phrase

And you just invoke it with python3 drjtst4.py.

Sample session output
in else part
text, word ct 1
{
"partial" : ""
}
in else part
text, word ct hey 1
{
"partial" : "hey"
}
in else part
text, word ct hey 1
{
"partial" : "hey"
}
in else part
text, word ct hey 1
{
"partial" : "hey"
}
in else part
Wake word detected. Now accumulating text.
text, word ct hey photo 2
Elapsed time: 0.0004639625549316406
{
"partial" : "hey photo"
}
in else part
text, word ct hey photo 2
Elapsed time: 0.003415822982788086
{
"partial" : "hey photo"
}
in else part
text, word ct hey photo 2
Elapsed time: 0.034906625747680664
{
"partial" : "hey photo"
}
in else part
text, word ct hey photo 2
Elapsed time: 0.09063172340393066
{
"partial" : "hey photo"
}
in else part
text, word ct hey photo 2
Elapsed time: 0.2488384246826172
{
"partial" : "hey photo"
}
in else part
text, word ct hey photo 2
Elapsed time: 0.33771753311157227
{
"partial" : "hey photo"
}
in else part
text, word ct hey photo place 3
Elapsed time: 0.7102789878845215
{
"partial" : "hey photo place"
}
in else part
text, word ct hey photo place 3
Elapsed time: 0.7134637832641602
{
"partial" : "hey photo place"
}
in else part
text, word ct hey photo player 3
Elapsed time: 0.8728365898132324
{
"partial" : "hey photo player"
}
in else part
text, word ct hey photo player 3
Elapsed time: 0.8759913444519043
{
"partial" : "hey photo player"
}
in else part
text, word ct hey photo play slideshow 4
Elapsed time: 1.0684640407562256
{
"partial" : "hey photo play slideshow"
}
in else part
text, word ct hey photo play slideshow 4
Elapsed time: 1.0879075527191162
{
"partial" : "hey photo play slideshow"
}
in else part
text, word ct hey photo play slideshow 4
Elapsed time: 1.3674390316009521
{
"partial" : "hey photo play slideshow"
}
in else part
text, word ct hey photo play slideshow 4
Elapsed time: 1.3706269264221191
{
"partial" : "hey photo play slideshow"
}
in else part
text, word ct hey photo play slideshow 4
Elapsed time: 1.5532972812652588
{
"partial" : "hey photo play slideshow"
}
in else part
text, word ct hey photo play slideshow 4
Elapsed time: 1.5963218212127686
{
"partial" : "hey photo play slideshow"
}
in else part
text, word ct hey photo play slideshow 4
Elapsed time: 1.74298095703125
{
"partial" : "hey photo play slideshow"
}
in else part
text, word ct hey photo play slideshow 4
Elapsed time: 1.842745065689087
{
"partial" : "hey photo play slideshow"
}
in else part
text, word ct hey photo play slideshow 4
Elapsed time: 1.9888567924499512
{
"partial" : "hey photo play slideshow"
}
in else part
text, word ct hey photo play slideshow 4
Elapsed time: 2.0897343158721924
{
"partial" : "hey photo play slideshow"
}
in first part
{
"text" : "hey photo play slideshow"
}
text, word ct 1
Elapsed time: 2.3853299617767334
This is the total text hey photo play slideshow
in else part
{
"partial" : ""
}
in else part
{
"partial" : ""
}
A word on accuracy

It isn’t Alexa or Google. No one expected it would be, right? But if you’re a native English speaker it isn’t too bad. You can see it trying to correct itself.

The desire to choose an uncommon wake word of three syllables is at direct odds with how neural networks are trained! So… although I desired my wake word to be “hey photo,” I also allow “a photo.” A photo was probably in their training set whereas Hey photo certainly was not. Hence the bias against recognizing a unique wake word. And no way will I re-train their model – way too much effort. But to lower false positives this phrase has to occur at the beginning of a spoken phrase.

Turning this into a smart speaker

You can see I’ve got all the pieces set up. At least I think I do! I’ve got my wake word. I don’t have natural language processing but I think I can forgo that. I have a place in the code where I print out the “final text.” That’s where the spoken command is perceived to have been uttered and and a potential action could be exectured at that point.

Dead ends

To be fleshed out later as time permits.

Conclusion

I have demonstrated how speech-to-text without use of complex cloud apis such as those provided by Amazon and Google can be easily achieved on an inexpensive raspberry pi.

I will be building on this facility in subsequent posts as I turn my RPi-powered slideshow into a slideshow which reacts to voice commands!

References and related

Vosk Installation (alphacephei.com)

Raspberry Pi slideshow

This conference USB mic works really well for me.

Categories
Python

Azure DevOps: use the api to copy logs to linux

Intro

As far as I can tell there’s no way to search through multiple pipeline logs with a single command. In linux it’s trivial. Seeing the lack of this basic functionality I decided to copy all my pipeline logs over to a linux server using the Azure DevOps (ADO) api.

The details

This is the main program which I’ve called get_raw_logs.py.

                    

#!/usr/bin/python3
# fetch raw log to local machine
# for relevant api section, see:
#https://learn.microsoft.com/en-us/rest/api/azure/devops/build/builds/get-build-log?view=azure-devops-rest-7.1
import urllib.request,json,sys
from datetime import datetime,timedelta
from modules import aux_modules

conf_file = sys.argv[1]

# pipeline uses UTC so we must follow suit or we will miss files
a_day_ago = (datetime.utcnow() - timedelta(days = 1)).strftime('%Y-%m-%dT%H:%M:%SZ')
print('a day ago (UTC)',a_day_ago)

#url = 'https://dev.azure.com/basf4ServicesCoreSystems/Connectivity/_apis/build/builds?minTime=2022-10-11T13:00:00Z&api-version=7.1-preview.7'

# dump config file into a dict
config_d = aux_modules.parse_config(conf_file)

url = config_d['url_base'] + config_d['organization'] + '/' + config_d['project'] + '/_apis/build/builds?minTime=' + a_day_ago + config_d['url_params']
#print('url',url)
req = urllib.request.Request(url)
req.add_header('Authorization', 'Basic ' + config_d['auth'])

# Get buildIds for pipeline runs from last 24 hours
with urllib.request.urlopen(req) as response:
   html = response.read()
txt_d = json.loads(html)
#{"count":215,"value":[{"id":xxx,buildNumber":"20221011.106","definition":{"name":"PAN-Usage4Mgrs-2"
value_l = txt_d['value']
for builds in value_l:
    buildId = builds['id']
    build_number = builds['buildNumber']
    build_def = builds['definition']
    name = build_def['name']
    #print('name,build_number,id',name,build_number,buildId)
    #print('this_build',builds)
    if name == config_d['pipeline1'] or name == config_d['pipeline2']:
        aux_modules.get_this_log(config_d,name,buildId,build_number)

In the modules directory this is aux_modules.py.

                    

import json
import os,urllib.request

def parse_config(conf_file):
# config file should be a json file
    f = open(conf_file)
    config_d = json.load(f)
    f.close()
    return config_d

def get_this_log(config_d,name,buildId,build_number):
# leaving out the api-version etc works better
#GET https://dev.azure.com/{organization}/{project}/_apis/build/builds/{buildId}/logs/{logId}?api-version=7.1-preview.2
#https://dev.azure.com/basf4ServicesCoreSystems/d6335c8e-f5b4-44a5-8f6c-7b17fe663a86/_apis/build/builds/44071/logs/7'
        buildId_s = str(buildId)
        log_name = config_d['log_dir'] + "/" + name + "-" + build_number
# check if we already got this one
        if os.path.exists(log_name):
            return
        #url = url_base + organization + '/' + project + '/_apis/build/builds/' + buildId_s + '/logs/' + logId + '?' + url_params
        url = config_d['url_base'] + config_d['organization'] + '/' + config_d['project'] + '/_apis/build/builds/' + buildId_s + '/logs/' + config_d['logId']
        print('url for this log',url)
        req = urllib.request.Request(url)
        req.add_header('Authorization', 'Basic ' + config_d['auth'])
        with urllib.request.urlopen(req) as response:
            html = response.read()
        #print('log',html)
        print("Getting (name,build_number,buildId,logId) ",name,build_number,buildId_s,config_d['logId'])
        f = open(log_name,"wb")
        f.write(html)
        f.close()

Unlike programs I usually write, some of the key logic resides in the config file. My config file looks something like this.

{
"organization":"drj4ServicesCoreSystems",
"project":"Connectivity",
"pipeline1":"PAN-Usage4Mgrs",
"pipeline2":"PAN-Usage4Mgrs-2",
"logId":"7",
"auth":"Yaskaslkasjklaskldslkjsasddenxisv=",
"url_base":"https://dev.azure.com/",
"url_params":"&api-version=7.1-preview.7",
"log_dir":"/var/tmp/rawlogs"
}

It runs very efficiently so I run it every three minutes.

In my pipelines, all the interesting stuff is in logId 7 so I’ve hardcoded that. It could have turned out differently. Notice I am getting the logs from two pipelines due to the limitation, discussed previously, that you can only run 1000 pipeline runs a week so I was forced to run two identical ones, staggered, every 12 minutes with pipeline-2 sleeping the first six minutes.

The auth is the base-64 encoded text for any:<my_auth_token>.

Conclusion

I show how to copy the logs over from Azure DevOps pipeline runs to a local Unix system where you can do normal cool linux commands on them.

References and related

Running an ADO pipeline more than 1000 times a week.

ADO Rest api reference section relevant for this post: https://learn.microsoft.com/en-us/rest/api/azure/devops/build/builds/get-build-log?view=azure-devops-rest-7.1

How to secure a sensitive variable in ADO.

Categories
IT Operational Excellence

MS Teams tip: how to avoid embarrassment of starting a meeting after it’s finished

Intro

You can only join a meetnig well after it’s started. You don’t want to be “that guy” who has started the meeting that has already finished, sending out an embarrassing alert to all meeting participants that you have started the meeting. So how do you prevent that?

The tip

It’s a little subtle and thus worth mentioning. From the MS Teams calendar (not from Outlook) look for the meeting. Click on it, but not on the Join button, and then click on Chat with particpants. See the screenshot.

Or you can right-click on the meeting and choose Chat with participants from the menu of available actions.

The chat, which is associated with the meeting or meeting series, will show when the meeting has ended!

Assumptions

Allow meeting chat is enabled for the meeting.

It is an internal meeting – not one for which you are waiting in the lobby.

Any participant can start the meeting.

Conclusion

We have shown how to always check to make sure you aren’t starting a Microsoft Teams meeting which is already over. It will spare you some embarrassment. I have even experienced and contributed to “meeting start ping-pong,” which is most embarrassing. By the time you join a meeting with no participants and realize it, it is already too late! The others will have been notified of your stupid action no matter how quick you are to leave the meeting.

Less frequently you will get a warning that a meeting is in progress and x participants have joined the meeting. But I have found that cannot be relied upon.

Categories
Cloud

Azure DevOps: pipeline tips

Intro

I’ve made a lot of mistakes and learned something from every one. I am trynig to pass on some of what I learned.

Limit of 1000 pipeline runs per week

This seems pretty crazy. In my unit we were going all gung-ho and imagining Azure DevOps pipelines as an elegant replacement for running cron jobs on our own linux servers. But something as simple as “I need to run this job every five minutes” seems to be overwhelming for a pipeline. What? Yes there is a hard limit of 1000 pipeline jobs a week. This limit is discussed here.

I wanted a job to run every six minutes, which will still hit that limit. So what I am trynig is to create two pipelines. Each is scheduled to run every 12 minutes. The yaml files are almost the same except in the one I sleep for six minutes. I also needed to remember to re-create the pipeline variables I was using.

Getting the raw logs from your pipeline runs

I wrote a little script to get the raw logs and copy them to a linux filesystem where I can use the linux command-line tools I know and love to examine them in bulk. The main point I wish to share right now is that it is not at all obvious that you need to use the get builds section of the api, not the log section! Who would have guessed? https://learn.microsoft.com/en-us/rest/api/azure/devops/build/builds/get-build-log?view=azure-devops-rest-7.1

Errors I am seeing in my pipeline

[error] We stopped hearing from agent dsc-adosonar-drjohns4servicescoresystems-agent-549c476959-whd72. Verify the agent machine is running and has a healthy network connection. Anything that terminates an agent process, starves it for CPU, or blocks its network access can cause this error. For more information, see: https://go.microsoft.com/fwlink/?linkid=846610

We still need to figure this one out. The error appears only randomly.

I also saw a lot of more subtle errors which amounted to my variables not being defined correctly in the yaml section. Indentation is important! I had variables set up secret environment variables amongst other things. The behavior which results does not always make it obvious what the root cause is.

Don’t run the pipeline for every commit

In your commit comment, put

[skip ci]

somewhere on its own line. This will avoid that the pipeline runs each time you do a commit, which quickly gets annoying.

References and related

How to use the Azure DevOps api to for instance fetch the raw logs

Microsoft’s api documentation pertinent to this topic:

https://learn.microsoft.com/en-us/rest/api/azure/devops/build/builds/get-build-log?view=azure-devops-rest-7.1

Categories
Cloud Python

Azure DevOps: How to work in a subfolder of a project

Intro

Our repo corresponds to a project. Within it are subfolders corresponding to individual apps we want to run in a pipeline.

Someone provided me with a starter yaml file to run my code in a pipeline. Originally my code was running just fine on my own linux server. In the pipeline, not so much as it became apparent it was expecting the current working directory to be the subfolder (directory in linux-speak) for references to modules, config files, etc. The documentation is kind of thin. So I spent hours checking things out and creating the solution which I now present.

The solution

The critical thing is to set the workingDirectory. Here is that section of the yaml file.

 script: python getlogdata.py 'PAN4-5min.aql'
  displayName: 'Run script'
  workingDirectory: $(System.DefaultWorkingDirectory)/PAN_Usage_4_Mgrs
  env:
    AUTH_TOKEN: $(auth_token)
#    PYTHONPATH: $(System.DefaultWorkingDirectory)/PAN_Usage_4_Mgrs/modules

Note that that PYTHONPATH environment variable is another possible way out – if all you need is to include modules, but it won’t help you with other things like finding your config file.

Errors

Now suppose you see an error like I got:

ImportError: cannot import name 'ZabbixMetric' from 'jhpyzabbix' (unknown location).

I had tried to put jhpyzabbix folder at the same level as my subfolder, so, right under the top project level. At first I was getting module not found errors. So I put back my PYTHONPATH like so

    PYTHONPATH: $(System.DefaultWorkingDirectory)/PAN_Usage_4_Mgrs:$(System.DefaultWorkingDirectory)

And that’s when I got that cannot import name error. Whar caused that is that although I had copied over the needed .py files to jhpyzabbix, I forgot one whose purpose seemed irrelevant to me. __init__.py. Turns out that tiny python file is quite important after all. School of hard knocks… It sets up the namespace mapping, I guess. To be concrete, mine looks like this:

from .api import ZabbixAPI, ZabbixAPIException, ssl_context_compat
from .sender import ZabbixMetric, ZabbixSender, ZabbixResponse
References and related

Passing secure variable in Azure DevOps to your program

Categories
Cloud

Securing a sensitive variable in Azure DevOps

Intro

I’m a newbie at Azure DevOps. They sort of have to drag me kicking and screaming to give up the comfort of my personal linux to endure the torture of learning something brand new. But I iguess that’s the new way so I gotta go along with it. I work within a project that has a repo. And we intend to run a pipeline. Question is, how to deal with sensitive parameters like passwords?

One approach

If you just do raw Internet searches you can fall into any number of rabbit holes. Key vault, anyone? How about relying on secure files within the library? I guess – very tentatively – that using a key vault might be the right way to deal with this issue, but it all depends on the ACLs available and I do not know that.. I also do not see a simple-minded way to set up a key vault. So what the guy who seems to know a lot more than I do is to set up a hidden variable for the pipeline itself.

The thing is that even that has its own gotchas. I find that depending on where you start from, you may ior may not see the option to declare a pipline variable as hidden.

If I am in the Pipeline section and looking at Recently Run Pipelines, and click on my pipeline, before I run it I can add variables. Doing it that way, you only get the option to include a name and Value. No option for declaring it to be hidden.

So how do you do it?

Instead of Run Pipline > variables go to Edit Pipeline > Variables. Then variables you create will have the option to be kept secret.

It is a bad idea to pass a sensitive information on the command line. Anyone with access to that agent could do a process listing to read the secret. So instead you use an environment variable. It’s a little tricky as you have to understand yaml variable interpolation versus script interpolation.

My secret variable is auth_token for the Zabbix api token. So in my yaml file I have a reference to it which sets up an environment variable:

- script: python Delete_Unused_VEdges/activity_check.py 'SA'
  displayName: 'Run script'
  env:
    AUTH_TOKEN: $(auth_token)

And in activity_check.py I read that environment variable like this:

token_zabbix = os.environ['AUTH_TOKEN']

And, voila, it’s all good.

But how secure is it really?

Question is, is this just performative security? Because I’m working with a project. Anyone else with access to the project could alter my python program temporarily to print out the value of the secret variable. I’m assuming they can both alter the repo I use as well as run a pipeline. Yes, they make it a tiny bit challenging because you need to break up a secret variable into two pieces in order to print it out, but come on. So maybe we’ve mostly achieved security by obscurity.

But again, I don’t really know the richness of this environment and perhaps more can be done to restrict who can alter the repo and run it in a pipeline.

Conclusion

People who know more than I, a newbie, have sugested a certain approach to dealing with sensitive variables with our Azure DevOps pipelines. I have described here what I as a newbie see as potential pitfalls as well as how to implement their chosen method.

Categories
CentOS Web Site Technologies

CentOS is dead

Intro

As my devoted followers will be aware, I nearly kiled myself converting my Centos 6 VM to CentOS 8. For instance see Upgrading WordPress brings a thicket of problems. That is an experience I only want to go through every 10 years, and fortunately, CentOS was just the right platform as its support was supposed to last 10 years I started this blog in either 2011 I believe. I went to CentOS 8 in 2020.

But instead of eight more good years, I’ve learned that CentOS is basically a dead product. EOL in industry parlance. IBM killed it. The last upgrades to CentOS 8 came at the end of 2021. There is a sort of CentOS, now called CentOS Stream, but it should be basically thought of a another Fedora. Probably IBM was losing too much money with people choosing CentOS (free) over RedHat paid subscription.

But anyway, I’ve come to resent how out-of-date the packages are on CentOS and I am much more favorable to plain old Debian linux, largely due to my work on the Raspberry Pi. There the packages like python are much more uptodate. I guess the support is for five years.

The other VM I would consider for my next iteration is Amazon Linux. It has a lot of what I need already installed, so less fuss. But I think they’re only supported for three years.

References and related

There is a snarky commentary about this topic which inspired this article. I don’t have the link right now but it is enlightening. I will post it if I ever find it.

Upgrading WordPress brings a thicket of problems

Categories
Linux

libavddvice.so.58 not found running ffprobe

Intro

I use ffmpeg regularly on my RPi 4. I’ve written several articles. For no apparent reason, today ffprobe, which I use to get the length or a recording, stopped working for no apparent reason. The error was something like

libavddvice.so.58 not found

I hadn’t done any upgrades or anything at all, I think.

The solution

$ sudo apt-get install libavdevice-dev

Even though it looked like it was already present as shown by a dpkg -l, running this command installed a bunch of related libraries and seemed to fix things up just fine.

ffmpeg version 4.3.4-0

Raspbian 11 bullseye

References and relate

https://drjohnstechtalk.com/blog/2021/10/from-audio-recording-to-youtube-with-two-button-clicks-and-a-raspberry-pi/

Categories
Consumer Tech Web Site Technologies

Starlink Internet service: a first look

Intro

Many of us were quite enthusiastically awaiting the availability of SpaceX’s Starlink Internet service. On paper it sounded promising. Now first results are in and the reality is far less impressive.

The details

I do not have this service but spoke with someone who does. He lives in Puerto Rico where the broadband option are limited. There’s the local cable company, then maybe some boutique services where you use microwave dishes, and this year, finally, Starlink. He had just a couple users on it. I think the net results are that it basically works, but with a big caveat. It sucks for real-time communication. And that’s precisely what he needed it for.

So you know when you’re streaming a movie, that downloads the movie in six(?) second chunks, so it’s a bit robust in the face of brief outages. But when you’re doing web conferencing an outage is very noticeable. And that’s what they experienced, time and again. Brief outages that interrupted their real-time applications. Perhaps lasting for a few seconds, but enough to spoil the broadcast.

Then one night, knowing their cable provider, Liberty, was out, they tested it again. It seemed fine at night. But during the day next day it failed in the same way – brief, disruptive outages.

Maybe some of it is due to holes in the satellite coverage and will get better as the fleet fills out. We’re not sure at this point.

And, yes, the dish was placed in a place where the app showed something like 98% visibility to the satellites in the sky.

Some interesting screenshots of what a Starlink IP looks like in Puerto Rico
ipinfo.io
ipchicken.com
speedtest results

That speedtest looks quite good to me!

Results of Starlink app for this actual user in Puerto Rico
Running PING to google.com shows a single dropped packet
A few words from the actual user

Liberty Cable is not working even after a change of the cable modem. So this past two weeks his household has been exclusively using Starlink. In his own words:

“The single most important thing to consider when using Starlink is how obstructed your northern facing view of the sky is. I am attaching a screenshot from my Starlink app. The red shows the obstructed area. My placement is 2.5% obstructed but I still get an interruption every 4 minutes the app says. In reality it might be every 20 minutes for a few seconds. 

“While my Liberty service has been out Starlink has been a life saver for us. A second user can still do her video calls but it will freeze during those 20-ish minute intervals for a few seconds. It’s not the end of the world for her but not totally idea.


“For me, my VPN will disconnect for those same few seconds and then will reconnect. If I’m entering a trade that can be a crucial few seconds while my vpn and software reconnects, but it’s workable. 


“The Starlink app is free and available for everyone to use. I would suggest that anyone who is interested in the service to first download the app and scan the sky where they think they have the freest point of view north. They will only get purely uninterrupted service if the app registers 100% obstacle-free view. The properties that are most suited for Starlink are the ones at the top of a hill, with a field, or a roof taller than the surrounding trees, especially the trees to the north. An obstructed view like mine is perfectly suitable for streaming movies as they tend to buffer a few minutes in advance, downloading files, and surfing the web. Without a completely obstructed view of the sky, video calls, VPN connection, Remote desktop connection, and online gaming will be interrupted in a frustrating manner. 


“I am also attaching a text file of my results from running a  ping -t to google.com from my Starlink connection. This test ran for about 25 minutes. The request time outs are the times when the Starlink satellite was not able to connect due to my obstructions. However, also notice that during these times it only lost 1 ping and was immediately able to reconnect. Again, somewhat frustrating but it’s a usable product. 

And during Hurricane Fiona?

Starlink performed like a champ during the hurricane. I assumed that coverage would be spotty during the drenching downpour but the user said no he was streaming Netflix. It was just a little more spotty than usual. Now that the island is without power as I write this, his Internet service is as good as usual and the day after the hurricane was a normal (remote) work day like any other.

Conclusion

Don’t throw away your cable modem*. In general as of this writing in June 2022, Starlink is a good solution for those working from home, but be prepared to be bumped every 20 minutes or so from your video conferencing or other real time uses. And of course it’s good for surfing the web or on-demand streaming.

I don’t cnosider this the final word however. There’s still hope. I’ll update this post if the quality of service ever improves.

*Unless you’re one of the many whose cable modem service isn’t all that great to begin with.

References and related

https://en.wikipedia.org/wiki/Starlink

This is a fascinating article providing insight into how the StarLink network of satellites is being built and the problems that can occur: https://www.msn.com/en-us/news/technology/destruction-event-from-sun-annihilated-dozens-of-spacex-satellites/ar-AA11TIwE?ocid=winp1taskbar&cvid=4c9b1b5306484cdcd2ab6bf99748bf01

Categories
Consumer Tech Web Site Technologies

Consumer tech: Edge new tab in Chinese

Intro

If you’ve ever had the misfortune to access a web site in China in your Edge browser, you may find that from that point onwards all your new tab pages display in Chinese despite of your best efforts to eradicate it.

The details

I was in that same boar until today. There are many bad leads out there on the Internet. In fact I never did find the solution on the Internet. I got it from a colleague.

You click on the three dots, go to Settings and search for reset.

Do the Reset. It is a little disruptive, as i have found. It does not delete everything, but it certainly resets some things. As soon as that’s done you will no longer have new tab pages be in Chinese.