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retico-googleasr

This project contains the incremental module for running Google Cloud ASR in a retico environment. Google ASR provides continuous speech recognition updates by updating the current prediction. As this is not in the correct format for incremental processing, the recognized speech gets incrementalized and only updates to the previous states are published. E.g.,

[UpdateType]        [text]             [stability]            [final]
UpdateType.ADD:     this               (0.8999999761581421) - False
UpdateType.ADD:     isn't a sentence   (0.8999999761581421) - False
UpdateType.REVOKE:  isn't a sentence   (0.8999999761581421) - False
UpdateType.ADD:     is a test sentence (0.0)                - True

Installing

To use the Automatic Speech Recognition module utilizing google cloud speech, you need to install the third-party package first.

For this, you may follow the first two steps of this tutorial.

pip install google-cloud-speech~=2.15

Important is, that you create your Google Application Credentials json file and save the path to that file into the global variable GOOGLE_APPLICATION_CREDENTIALS (look for the "Before you begin" section on the tutorial page).

After that you can install the package with

$ pip install retico-googleasr

Documentation

Sadly, there is no proper documentation for retico-googleasr right now, but you can start using the GoogleASRModule like this:

from retico_core import *
from retico_googleasr import *


msg = []


def callback(update_msg):
    global msg
    for x, ut in update_msg:
        if ut == UpdateType.ADD:
            msg.append(x)
        if ut == UpdateType.REVOKE:
            msg.remove(x)
    txt = ""
    committed = False
    for x in msg:
        txt += x.text + " "
        committed = committed or x.committed
    print(" " * 80, end="\r")
    print(f"{txt}", end="\r")
    if committed:
        msg = []
        print("")


m1 = audio.MicrophoneModule()
m2 = GoogleASRModule("en-US")  # en-US or de-DE or ....
m3 = debug.CallbackModule(callback=callback)

m1.subscribe(m2)
m2.subscribe(m3)

network.run(m1)

print("Running")
input()

network.stop(m1)

Metadata

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