ngchat-speech-sdk 0.1.5

ngChat Speech SDK: Realize ngChat Speech-to-Text recognition and Text-to-Speech synthesis.

ngChat Speech SDK

Please contact [e-mail] if you have any questions.

Speech-to-Text Example:

Prerequisites

You will need a ngChat speech-to-text service url to run this example. Please contact [e-mail] and apply for it.

Install and import

To install ngChat Speech SDK:

pip install ngchat-speech-sdk

To import ngChat Speech SDK:

import ngchat_speech.speech as speechsdk

Recognition

In the example below, we show how to recognize speech from an audio file. You can also apply recognition to an audio stream.

Speech Configuration

Use the following code to create SpeechConfig (contact [e-mail] for the service host):

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

Audio Configuration

Use the following code to create AudioConfig.

    # Code commented out is an example for recognition on an audio stream.
    # audio_format = speechsdk.audio.AudioStreamFormat(
    #     samples_per_second=16000, bits_per_sample=16, channels=1)
    # audio_stream = speechsdk.audio.PushAudioInputStream(stream_format=audio_format)
    # audio_config = speechsdk.audio.AudioConfig(stream=audio_stream)
    audio_config = speechsdk.audio.AudioConfig(filename="test.wav")

Recognizer initialization

SpeechRecognizer can be initialzed as follows:

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

Callbacks connection

SpeechRecognizer has 5 kinds of callbacks:

• Recognizing - called when recognition is in progress.
• Recognized - called when a single utterance is recognized.
• Canceled - called when a continuous recognition is interrupted.
• Session_started - called when a recognition session is started.
• Session_stopped - called when a recognition session is stopped.

To connect the callbacks:

    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}'))

Recognizing speech

Now it is 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. It stops recognition after a single utterance is recognized.
• Continuous recognition (async) - Asynchronously initiates continuous recognition on an audio stream. Recognition results are available through callback functions. To stop the continuous recognition, call stop_continuous_recognition_async().

    # Code commented out is for recognition on an audio stream.
    # speech_recognizer.start_continuous_recognition_async()
    speech_recognizer.recognize_once()

Putting everything together

Now, put everything together and run the example:

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_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()

Text-to-Speech Example:

Prerequisites

You will need a ngChat text-to-speech service url to run this example. Please contact [e-mail] and apply for it.

Install and import

To install ngChat Speech SDK:

pip install ngchat-speech-sdk

To import ngChat Speech SDK:

import ngchat_speech.speech as speechsdk

Synthesis

In the example below, we show how to synthesize text to generate an audio file. You can also receive synthesis results from an audio stream.

Speech Configuration

Use the following code to create SpeechConfig (contact [e-mail] for the service host):

    speech_config = speechsdk.SpeechConfig(
        host="ws://NGCHAT_TTS_SERVER"
    )

Audio Configuration

Use the following code to create AudioOutputConfig.

    import ngchat_speech.audio as audio
    # Code commented out is an example for receiving synthesis results from an audio stream.
    # audio_stream = audio.AudioOutputStream()
    # audio_config = audio.AudioOutputConfig(stream=audio_stream)
    audio_config = audio.AudioOutputConfig(filename="output.wav")

Synthesizer initialization

Synthesizer can be initialzed as follows:

    speech_synthesizer = speechsdk.SpeechSynthesizer(
        speech_config=speech_config,
        audio_config=audio_config
    )

Callbacks connection

SpeechSynthesizer has 4 kinds of callbacks:

• Synthesis_started - called when synthesis is started.
• Synthesizing - called when each time part of synthesis result is given.
• Synthesis_completed - called when all text was synthesized.
• Synthesis_canceled - called when synthesis is interrupted.

To connect the callbacks:

    speech_synthesizer.synthesis_started.connect(
        lambda : print("synthesis started"))
    speech_synthesizer.synthesizing.connect(
        lambda : print("synthesizing"))
    speech_synthesizer.synthesis_completed.connect(
        lambda : print("synthesis completed"))
    speech_synthesizer.synthesis_canceled.connect(
        lambda : print("synthesis canceled"))

Synthesizing text

Now it is ready to run SpeechSynthesizer. There are two ways to run SpeechSynthesizer:

• Synchronized - Perform synthesis until got all result.
• Asynchronized - Start synthesis and return a speechsdk.ResultFuture, which you could call its get() function to wait and get synthesis result.

    # Code commented out is for synchronized synthesis
    # result = speech_synthesizer.speak_text("Input your text to synthesize here.")
    result = speech_synthesizer.speak_text_async("Input your text to synthesize here.").get()
    # Code commented out is an example for reading synthesis result from an audio stream.
    # audio_data = audio_stream.read()

Judge result reason:

Both synchronized and asynchronized ways return a speechsdk.SpeechSynthesisResult, which has result to judge if synthesis was completed successfully:

    if result.reason == speechsdk.ResultReason.ResultReason_SynthesizingAudioCompleted:
        print("finished speech synthesizing")

Putting everything together

Now, put everything together and run the example:

from ngchat_speech import speech as speechsdk
from ngchat_speech import audio as audio

if __name__ == "__main__":
    speech_config = speechsdk.SpeechConfig(
        host="ws://NGCHAT_TTS_SERVER"
    )
    audio_config = audio.AudioOutputConfig(filename="output.wav")
    speech_synthesizer = speechsdk.SpeechSynthesizer(
        speech_config=speech_config,
        audio_config=audio_config
    )
    speech_synthesizer.synthesis_started.connect(
        lambda : print("synthesis started"))
    speech_synthesizer.synthesizing.connect(
        lambda : print("synthesizing"))
    speech_synthesizer.synthesis_completed.connect(
        lambda : print("synthesis completed"))
    speech_synthesizer.synthesis_canceled.connect(
        lambda : print("synthesis canceled"))

    # result = speech_synthesizer.speak_text("Seasalt.ai is a service company focusing on multi-modal AI solutions.")
    result = speech_synthesizer.speak_text_async("Seasalt.ai is a service company focusing on multi-modal AI solutions.").get()

    if result.reason == speechsdk.ResultReason.ResultReason_SynthesizingAudioCompleted:
        print("finished speech synthesizing")