How to push float32 array to audioInputStream using pullAudioInputStreamCallback

Question

How to push float32 array to audioInputStream using pullAudioInputStreamCallback

Sandeep Pradeep 20


i have taken realtime audio data and used as float32 array how to convert it to azure AudioStreamInput

import numpy as np
import azure.cognitiveservices.speech as speechsdk

class NumpyAudioStream(speechsdk.audio.PullAudioInputStreamCallback):
    def __init__(self, audio_array):
        self.audio_array = audio_array
        self.position = 0

    def read(self, buffer, offset, count):
        remaining = len(self.audio_array) - self.position
        to_read = min(remaining, count)
        buffer[:to_read] = self.audio_array[self.position:self.position+to_read]
        self.position += to_read
        return to_read
Tried this but 'NumpyAudioStream' object has no attribute '_handle' error occuring

i have afloat32 array how to create an Azure AudioInputStream

YutongTie-MSFT 39,441 Reputation points

2023-11-11T09:51:28.2633333+00:00
@Sandeep Pradeep

Thanks for reaching out to us, to create an AudioInputStream from a float32 array using the PullAudioInputStreamCallback, you can modify the NumpyAudioStream class as follows:

import numpy as np import azure.cognitiveservices.speech as speechsdk class NumpyAudioStream(speechsdk.audio.PullAudioInputStreamCallback): def __init__(self, audio_array): self.audio_array = audio_array self.position = 0 def read(self, buffer, offset, count): remaining = len(self.audio_array) - self.position to_read = min(remaining, count) buffer[:to_read] = self.audio_array[self.position:self.position+to_read] self.position += to_read return to_read # Create a float32 array audio_data = np.random.rand(16000).astype(np.float32) # Create an AudioConfig object audio_config = speechsdk.audio.AudioConfig(stream=NumpyAudioStream(audio_data)) # Create an AudioInput object audio_input = speechsdk.audio.AudioInput(stream=audio_config)

In this example, we first create a float32 array called audio_data. We then create an AudioConfig object using the NumpyAudioStream class, passing in the audio_data array. Finally, we create an AudioInput object using the AudioConfig object.

Note that the NumpyAudioStream class is defined as a subclass of PullAudioInputStreamCallback, which is used to provide a callback function that is called by the AudioConfig object to read audio data from the stream. The read method of the NumpyAudioStream class reads data from the audio_array attribute and writes it to the buffer argument, which is then passed to the AudioConfig object.
Sandeep Pradeep 20 Reputation points

2023-11-11T10:20:52.9766667+00:00

@YutongTie-MSFT Thanks for the response. I was trying to input real time audio to the stream and convert it to text using azure speech to text. Now i have used pushAudioInputStream and used the stream to create audio.transcribing object and transcribe the audio stream but the result is not correct. Either the audio is not correctly pushing the stream or its not recognising the audio and its cancelling the start_transcription_async call. Please help on this.

YutongTie-MSFT 39,441 Reputation points

2023-11-11T09:51:28.2633333+00:00

@Sandeep Pradeep

Thanks for reaching out to us, to create an AudioInputStream from a float32 array using the PullAudioInputStreamCallback, you can modify the NumpyAudioStream class as follows:

import numpy as np import azure.cognitiveservices.speech as speechsdk class NumpyAudioStream(speechsdk.audio.PullAudioInputStreamCallback): def __init__(self, audio_array): self.audio_array = audio_array self.position = 0 def read(self, buffer, offset, count): remaining = len(self.audio_array) - self.position to_read = min(remaining, count) buffer[:to_read] = self.audio_array[self.position:self.position+to_read] self.position += to_read return to_read # Create a float32 array audio_data = np.random.rand(16000).astype(np.float32) # Create an AudioConfig object audio_config = speechsdk.audio.AudioConfig(stream=NumpyAudioStream(audio_data)) # Create an AudioInput object audio_input = speechsdk.audio.AudioInput(stream=audio_config)

In this example, we first create a float32 array called audio_data. We then create an AudioConfig object using the NumpyAudioStream class, passing in the audio_data array. Finally, we create an AudioInput object using the AudioConfig object.

Note that the NumpyAudioStream class is defined as a subclass of PullAudioInputStreamCallback, which is used to provide a callback function that is called by the AudioConfig object to read audio data from the stream. The read method of the NumpyAudioStream class reads data from the audio_array attribute and writes it to the buffer argument, which is then passed to the AudioConfig object.
Sandeep Pradeep 20 Reputation points

2023-11-11T10:20:52.9766667+00:00

@YutongTie-MSFT Thanks for the response. I was trying to input real time audio to the stream and convert it to text using azure speech to text. Now i have used pushAudioInputStream and used the stream to create audio.transcribing object and transcribe the audio stream but the result is not correct. Either the audio is not correctly pushing the stream or its not recognising the audio and its cancelling the start_transcription_async call. Please help on this.

How to push float32 array to audioInputStream using pullAudioInputStreamCallback

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