node-record-lpcm16 | bit signed-integer linear pulse modulation code
kandi X-RAY | node-record-lpcm16 Summary
kandi X-RAY | node-record-lpcm16 Summary
:microphone: Records a 16-bit signed-integer linear pulse modulation code encoded audio file.
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QUESTION
Okay, so I've been trying to do this for a long time but I just can't find a solution. I'm building a personal Voice Assistant that only records when a hotword is detected, and everything until here works fine. To record the audio, I'm using the npm package node-record-lcpm16. I can't seem to find a solution to pause or stop(and start again) the recording. On the npm website of the audiorecorder there is a function specified that says recording.stop() but it doesn't work for me. My code right now is:
...ANSWER
Answered 2021-Feb-25 at 16:09I've played about with your code.. it's definitely a fun project to play with!
I would suggest maybe just modifying the code to record to a buffer, then send that to the google speech recognition engine.
The reason recording.stop() was probably not working for you is that you were calling it on the stream. If we separate the recording and recordingStream variables we can control the flow better.
I've updated the code so when we get the hotword, we stop recording, recognize the speech, then start recording again.
QUESTION
I want to link Google Speech to Text engine with my microphone.
I found this page, copied the code to my renderer.ts
file (uncommented the lines with const
), but when running - getting the following error, due to line 7 (const client = new speech.SpeechClient();
):
And yes, I did try to run both yarn install --force
(as I'm primarily using Yarn) and npm rebuild
, as well as yarn add grpc
, yet the problem still occurs.
renderer.ts
:
ANSWER
Answered 2019-Mar-06 at 19:18In order to use this library on Electron you have to add extra installation arguments to specifically install for Electron. Electron has generic instructions for using native Node modules.
For gRPC in particular, with the version of Electron you have, you should be able to get it by running
QUESTION
I just started with node.js and am trying to connect the generated microphone stream from the browser with the google speech api running on my node server and the microphone-stream
package.
I successfully packed the necessary modules with browserify, but now don't know how to proceed. I got the microphone stream to work on the node server
as well (as explained here: Streaming Speech Recognition on an Audio Stream ).
How can I transmit the audiostream? I read about using websockets in one issue, but didn't really understand if it's the right way in my case. Or RPC?
For now I'm using these packages on the server:
...ANSWER
Answered 2018-Apr-09 at 09:19I built a playground to tackle this task. It doesn't use any of the previous plugins (node record 16 / microphone-stream / ...) but sends a 16 bit audio stream to the node server via socket.io.
https://github.com/vin-ni/Google-Cloud-Speech-Node-Socket-Playground
QUESTION
I've jacked the following example code (recognize.js) from https://github.com/GoogleCloudPlatform/nodejs-docs-samples/tree/master/speech (Requires auth with this):
...ANSWER
Answered 2017-Feb-17 at 11:58I'm not 100% certain, but it sounds like there could be multiple explanations:
The request is asking for a "single utterance" (StreamingRecognitionConfig)
This seems unusual because the default appears to be
false
. However it can't hurt to be explicit in the request (const request = { singleUtterance: false, config: {...} }
)You're running into the client-defined timeout (createRecognizeStream).
This also seems a bit strange because I'm guessing you're not sitting there talking for 60 seconds straight and then stopping after such a long time.
Your mic is closing the stream which gets propagated back to the Speech client.
This seems a bit more plausible, but I'm not 100% confident.
If you can record what you're saying into the microphone and reproduce this problem with a file sent via the createRecognizeStream
method (rather than a live audio stream), that eliminates the last item, and would make it easier to diagnose.
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