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This is very impressive. I'm the owner of Broadcastify.com, where presumably these streams are being transcribed from. We've dabbled in this space and looked a

This is very impressive. I'm the owner of Broadcastify.com, where presumably these streams are being transcribed from. We've dabbled in this space and looked at real-world approaches to taking something like this to market, but transcribing 7000+ streams to text seems like an expensive (computational) and ($$) effort that needs a lot of investigation. Note to mention that the individual lexicons between streams are drastically different. I wonder how the developer has done the integration to our streams... because I never heard from them :)

robbiet480 6y ago
Hey Lindsay, I'm the one who just added EBRCS to Calls. Wondering if a solution to both cost problems would be to (optionally) have submitters upload a transcript along with each call? Could build a model into trunk-recorder maybe?
- blantonl 6y ago
  That might be an option, but we'd have to somehow get trained models down to the client, which is one of the issues. We're working on client ingest models now that work on more of a "tasking" perspective, where someone deploys a device that is GPS enabled and then we send an ingest task to fill in coverage, start new coverage, etc. But this is predicated on low cost ingest devices (read: RPi and RTL sticks) which might not have the horsepower needed for transcription at the client level.
  - johann8384 6y ago
    That would be cool, kind of like GroundStation or SatNOGS
lunixbochs 6y ago
I prototyped this concept too, at https://feeds.talonvoice.com https://feeds.talonvoice.com with prohibitively expensive Google speech recognition, but also have a feature for users to listen and fix transcriptions. If murph was anything like me they probably paid for broadcastify and tailed a couple of the static mp3 feeds. My plan was to collect user transcription corrections on my site then train my own inexpensive models on them. The open-source speech tech I work on can do passable transcription at close to 100x faster than realtime on a quad core desktop CPU (or 200 simultaneous streams per 4-core box at 50% activity). With higher quality transcription it's closer to 10-20x faster than realtime. For your case you could also try to push some of the computation down to the uploading machine. These models can run on a raspberry pi. I think the biggest work for a new effort here is going to be building local language models and collecting transcribed audio to train on. However, there have been a couple of incredible advances in the last year for semi-supervised speech recognition learning, where we can probably leverage your 1 year backlog as "unsupervised training data" while only having a small portion of it properly transcribed. The current state-of-the-art paper uses around 100 hours of transcribed audio and 60,000 hours of unlabeled audio, and I bet you could push the 100h requirement down with a good language model and mixing in existing training data from non-radio sources.
- blantonl 6y ago
  Our new project, Broadcastify Calls, might be a better fit for this. Instead of 24x7 live streams, we capture and ingest every individual call as a compressed audio file from SDRs (software defined receivers) We can then ingest and present back to consumers playback, rewind, playlist, of those calls. We're now capturing over 100 systems and 800-900 calls a minute... as we solidify the architecture it will be our new direction for how we capture and disseminate public safety audio (Police Scanners) https://www.broadcastify.com/calls https://www.broadcastify.com/calls
  - lunixbochs 6y ago
    The source repo to feeds.talonvoice.com includes a test ingestor that scrapes your calls API and uploads the src/dst info with the transcription, I haven't tested it live though.
  - p0sixlang 6y ago
    Hey Blatoni, big fan, and software engineer here. Any way you could add Rochester, NY (Monroe County Sheriff, and RPD) to the list of supported calls? I have an RTL SDR, but haven't been able to spend the time figuring out how to decrypt the Phase II trunking.
    - blantonl 6y ago
      You can get started as a calls ingest provider here: https://wiki.radioreference.com/index.php/Broadcastify-Calls https://wiki.radioreference.com/index.php/Broadcastify-Calls
    - robotastic 6y ago
      Hop on to https://gitter.im/trunk-recorder/Lobby https://gitter.im/trunk-recorder/Lobby if you are having trouble getting the https://github.com/robotastic/trunk-recorder https://github.com/robotastic/trunk-recorder software running. Trunk Recorder puts a wrapper around the OP25 software and lets you capture all of the audio from a radio system using an SDR.
  - 6y ago
godzillabrennus 6y ago
You could conceivably do this using the text to speech recognition on a Mac using Loopback to capture the stream to a microphone input. https://rogueamoeba.com/loopback/ https://rogueamoeba.com/loopback/ Someone clever enough could create containers to run the software locally and have many loops running off many streams to many instances of the audio to text feature.
- lunixbochs 6y ago
  Conventional speech recognition will not have very good accuracy for this sort of task out of the box. You will basically need to do local (as in, based on map location) language modeling, and should probably do custom acoustic modeling as well (training a neural network on what radio speech sounds like).
  - crazygringo 6y ago
    Did you look at the transcripts? They do not have very good accuracy. A better solution probably should do those things; this one I'm assuming is not.
    - lunixbochs 6y ago
      https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html > Please don't comment on whether someone read an article. "Did you even read the article? It mentions that" can be shortened to "The article mentions that." Yes, I looked the website, and I also have my own website that does the same thing in a very similar manner. My comment was entirely in response to the suggestion Mac speech recognition be used for this. It should not be used for this. Based on previous experiments I have personally performed, it would be even worse than the website's accuracy. I then pointed out what a good solution might look like (and neither my website nor the linked website do the good solution yet)
      - jcims 6y ago
        Assuming you tried Amazon Transcribe? How did it fare?
artemisyna 6y ago
Not sure how easy/difficult this would be from am implementation perspective, but perhaps transcription could be provided as a pay-as-you-go service. Ie, users could pay into a pool for live transcription of a stream for a certain period of time or to retroactively transcribe specific streams. I'd have to imagine that stream listening follows some sort of power (or otherwise 80/20) law, so hopefully that would help with the expense?
ciarannolan 6y ago
Not exactly related to this specific post, but do you worry about the slow transition to encrypted comms that emergency departments are making?
bertmuthalaly 6y ago
Have you taken a look at the output? I selected the NYC scanner and found many examples like this: June 8, 2020 9:03 PM EDT: "Google Launcher new job and I want to play better third-party colder or does the people from the vegetable okay"
optimumsuave 6y ago
Thank you for the kind words. My team and I simply want to help people and create accountability/transparency. We decided to ask for forgiveness on this project - we do in fact have a premium account with you guys! ffmpeg records and segments your streams, sox removes silence from scanners, Google transcribes, redis serves it all up quickly! A broadcastify.com premium account is not not a great excuse, but I would love to have a conversation at length with you and your team! How do we get in contact? Thanks again!
- robotastic 6y ago
  Feel free to add something like this to some of the feeds from http://openmhz.com http://openmhz.com I can give you some pointers on how to pull down the streams of audio. They are already chopped into M4A files.
coffeeboy27 6y ago
Hey I want to say that I love Broadcastify for listening to my local police and fire scanners so thank you for providing that free service without requiring app downloads and so on. Awesome work! I will say though I recently noticed that during the recent unrest in my city that the stream had a caption along the lines of 'police are using encrypted channels' which is understandable but disappointing from the perspective of a citizen looking for transparency. I realize both the possible legal and technical difficulty of implementing something like this but have you had any conversations about how to maybe combat this? Times of unrest are not only a massive opportunity for Broadcastify to grow its user base but it's also when transparency is at its peak importance.

robbiet480 6y ago

Hey Lindsay, I'm the one who just added EBRCS to Calls. Wondering if a solution to both cost problems would be to (optionally) have submitters upload a transcript along with each call? Could build a model into trunk-recorder maybe?

blantonl 6y ago
That might be an option, but we'd have to somehow get trained models down to the client, which is one of the issues. We're working on client ingest models now that work on more of a "tasking" perspective, where someone deploys a device that is GPS enabled and then we send an ingest task to fill in coverage, start new coverage, etc. But this is predicated on low cost ingest devices (read: RPi and RTL sticks) which might not have the horsepower needed for transcription at the client level.
- johann8384 6y ago
  That would be cool, kind of like GroundStation or SatNOGS

lunixbochs 6y ago

I prototyped this concept too, at https://feeds.talonvoice.com https://feeds.talonvoice.com with prohibitively expensive Google speech recognition, but also have a feature for users to listen and fix transcriptions. If murph was anything like me they probably paid for broadcastify and tailed a couple of the static mp3 feeds. My plan was to collect user transcription corrections on my site then train my own inexpensive models on them. The open-source speech tech I work on can do passable transcription at close to 100x faster than realtime on a quad core desktop CPU (or 200 simultaneous streams per 4-core box at 50% activity). With higher quality transcription it's closer to 10-20x faster than realtime. For your case you could also try to push some of the computation down to the uploading machine. These models can run on a raspberry pi. I think the biggest work for a new effort here is going to be building local language models and collecting transcribed audio to train on. However, there have been a couple of incredible advances in the last year for semi-supervised speech recognition learning, where we can probably leverage your 1 year backlog as "unsupervised training data" while only having a small portion of it properly transcribed. The current state-of-the-art paper uses around 100 hours of transcribed audio and 60,000 hours of unlabeled audio, and I bet you could push the 100h requirement down with a good language model and mixing in existing training data from non-radio sources.

blantonl 6y ago
Our new project, Broadcastify Calls, might be a better fit for this. Instead of 24x7 live streams, we capture and ingest every individual call as a compressed audio file from SDRs (software defined receivers) We can then ingest and present back to consumers playback, rewind, playlist, of those calls. We're now capturing over 100 systems and 800-900 calls a minute... as we solidify the architecture it will be our new direction for how we capture and disseminate public safety audio (Police Scanners) https://www.broadcastify.com/calls https://www.broadcastify.com/calls
- lunixbochs 6y ago
  The source repo to feeds.talonvoice.com includes a test ingestor that scrapes your calls API and uploads the src/dst info with the transcription, I haven't tested it live though.
- p0sixlang 6y ago
  Hey Blatoni, big fan, and software engineer here. Any way you could add Rochester, NY (Monroe County Sheriff, and RPD) to the list of supported calls? I have an RTL SDR, but haven't been able to spend the time figuring out how to decrypt the Phase II trunking.
  - blantonl 6y ago
    You can get started as a calls ingest provider here: https://wiki.radioreference.com/index.php/Broadcastify-Calls https://wiki.radioreference.com/index.php/Broadcastify-Calls
  - robotastic 6y ago
    Hop on to https://gitter.im/trunk-recorder/Lobby https://gitter.im/trunk-recorder/Lobby if you are having trouble getting the https://github.com/robotastic/trunk-recorder https://github.com/robotastic/trunk-recorder software running. Trunk Recorder puts a wrapper around the OP25 software and lets you capture all of the audio from a radio system using an SDR.
- 6y ago

godzillabrennus 6y ago

You could conceivably do this using the text to speech recognition on a Mac using Loopback to capture the stream to a microphone input. https://rogueamoeba.com/loopback/ https://rogueamoeba.com/loopback/ Someone clever enough could create containers to run the software locally and have many loops running off many streams to many instances of the audio to text feature.

lunixbochs 6y ago
Conventional speech recognition will not have very good accuracy for this sort of task out of the box. You will basically need to do local (as in, based on map location) language modeling, and should probably do custom acoustic modeling as well (training a neural network on what radio speech sounds like).
- crazygringo 6y ago
  Did you look at the transcripts? They do not have very good accuracy. A better solution probably should do those things; this one I'm assuming is not.
  - lunixbochs 6y ago
    https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html > Please don't comment on whether someone read an article. "Did you even read the article? It mentions that" can be shortened to "The article mentions that." Yes, I looked the website, and I also have my own website that does the same thing in a very similar manner. My comment was entirely in response to the suggestion Mac speech recognition be used for this. It should not be used for this. Based on previous experiments I have personally performed, it would be even worse than the website's accuracy. I then pointed out what a good solution might look like (and neither my website nor the linked website do the good solution yet)
    - jcims 6y ago
      Assuming you tried Amazon Transcribe? How did it fare?

artemisyna 6y ago

Not sure how easy/difficult this would be from am implementation perspective, but perhaps transcription could be provided as a pay-as-you-go service. Ie, users could pay into a pool for live transcription of a stream for a certain period of time or to retroactively transcribe specific streams. I'd have to imagine that stream listening follows some sort of power (or otherwise 80/20) law, so hopefully that would help with the expense?

ciarannolan 6y ago

Not exactly related to this specific post, but do you worry about the slow transition to encrypted comms that emergency departments are making?

bertmuthalaly 6y ago

Have you taken a look at the output? I selected the NYC scanner and found many examples like this: June 8, 2020 9:03 PM EDT: "Google Launcher new job and I want to play better third-party colder or does the people from the vegetable okay"

optimumsuave 6y ago

Thank you for the kind words. My team and I simply want to help people and create accountability/transparency. We decided to ask for forgiveness on this project - we do in fact have a premium account with you guys! ffmpeg records and segments your streams, sox removes silence from scanners, Google transcribes, redis serves it all up quickly! A broadcastify.com premium account is not not a great excuse, but I would love to have a conversation at length with you and your team! How do we get in contact? Thanks again!

robotastic 6y ago
Feel free to add something like this to some of the feeds from http://openmhz.com http://openmhz.com I can give you some pointers on how to pull down the streams of audio. They are already chopped into M4A files.

coffeeboy27 6y ago

Hey I want to say that I love Broadcastify for listening to my local police and fire scanners so thank you for providing that free service without requiring app downloads and so on. Awesome work! I will say though I recently noticed that during the recent unrest in my city that the stream had a caption along the lines of 'police are using encrypted channels' which is understandable but disappointing from the perspective of a citizen looking for transparency. I realize both the possible legal and technical difficulty of implementing something like this but have you had any conversations about how to maybe combat this? Times of unrest are not only a massive opportunity for Broadcastify to grow its user base but it's also when transparency is at its peak importance.