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ngChat Speech to Text and Text to Speech SDK

Project description

ngChat Speech to Text and Text to Speech SDK

Welcome to ngChat, Next Generation Chat, a revolutionary enterprise conversational platform that aims to:

  1. addressing issues from the first version of NLU/ChatFlow, and
  2. adding significant new features that support enterprise dialogue applications for the next 5 years.

To know more, please visit Seasalt.ai

Example to use ngChat Speech to Text SDK:

Prerequisites

You'll need a ngchat speech-to-text server url to run this example. Please contact Seasalt.ai to have one.

Install and import the Speech SDK

First you'll need to install the Speech SDK. pip install ngchat-speech-sdk

After the Speech SDK is installed, import it inot your Python project with this. import ngchat_speech.speech as speechsdk

Create a speech configuration

To call the Speech service using the Speech SDK, you need to create a SpeechConfig. You'll need a ngchat speech-to-text server url to run this example. Please contact Seasalt.ai to have one.

    speech_config = speechsdk.SpeechConfig(
        host="ws://NGCHAT_STT_SERVER/client/ws/speech"
    )

Recognize from a file

In this example, we'll show how to recognize speech from an audio file, if you want to recognize a stream, you'll need to use SpeechRecognizer.start_continuous_recognition_async() instead of SpeechRecognizer.recognize_once(). Create an AudioConfig and use the filename parameter.

    audio_stream = speechsdk.audio.PushAudioInputStream()
    audio_config = speechsdk.audio.AudioConfig(
        filename="test.wav"
    )

Initialize a recognizer

After you've created a SpeechConfig and an AudioConfig, the next step is to initialize a SpeechRecognizer.

    speech_recognizer = speechsdk.SpeechRecognizer(
        speech_config=speech_config,
        audio_config=audio_config
    )

Connect callbacks to recognizer

SpeechRecognizer has 5 kinds of callbacks.

  • Recognizing - called when some words were recognized, but not finished recognizing a single utterance.
  • Recognized - called when a single utterance was recognized.
  • Canceled - called when a continuous recognition was interrupted.
  • Session_started - called when a recognition sesstion was started.
  • Session_stopped - called when a recognition sesstion was stopped.
    speech_recognizer.recognizing.connect(
        lambda evt: print(f"Recognizing: {evt.result.text}"))
    speech_recognizer.recognized.connect(
        lambda evt: print(f'Recognized: {evt.result.text}'))
    speech_recognizer.canceled.connect(
        lambda evt: print(f'Canceled: {evt}'))
    speech_recognizer.session_started.connect(
        lambda evt: print(f'Session_started: {evt}'))
    speech_recognizer.session_stopped.connect(
        lambda evt: print(f'Session_stopped: {evt}'))

Recognize speech

Now you're ready to run SpeechRecognizer. SpeechRecognizer has two ways for speech recognition.

  • Single-shot recognition - Performs recognition once. This is to recognize a single audio file. Stop recognizing after a single utterance is recognized.
  • Continuous recognition (async) - Asynchronously initiates continuous recognition operation. Connect to Recognizing and Recognized callbacks to receive recognition results. To stop asynchronous continuous recognition, call stop_continuous_recognition_async(). speech_recognizer.recognize_once()

Put all together

We put all these steps together, the example code to test ngChat Speech SDK will look like this.

import speech as speechsdk
import audio as audio
import asyncio
import threading
import sys
import time

if __name__=="__main__":
    # this is an example to show how to use the ngChat Speech SDK to recognize once

    try:
        speech_config = speechsdk.SpeechConfig(
            host="ws://NGCHAT_STT_SERVER/client/ws/speech"
        )
        audio_stream = audio.PushAudioInputStream()
        audio_config = audio.AudioConfig(filename="test.wav")
        speech_recognizer = speechsdk.SpeechRecognizer(
            speech_config=speech_config,
            audio_config=audio_config
        )

        speech_recognizer.recognizing.connect(
            lambda evt: print(f"Recognizing: {evt.result.text}"))
        speech_recognizer.recognized.connect(
            lambda evt: print(f'Recognized: {evt.result.text}'))
        speech_recognizer.canceled.connect(
            lambda evt: print(f'Canceled: {evt}'))
        speech_recognizer.session_started.connect(
            lambda evt: print(f'Session_started: {evt}'))
        speech_recognizer.session_stopped.connect(
            lambda evt: print(f'Session_stopped: {evt}'))

        speech_recognizer.recognize_once()
        time.sleep(3)

    except KeyboardInterrupt:
        print("Caught keyboard interrupt. Canceling tasks...")
    except Exception as e:
        print(f"Exception: {e}")
    finally:
        sys.exit()

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