kiruthika162003/-ibm-watson-speech-to-text-

IBM-Watson-Speech-to-Text

Implementing IBM Watson Speech to Text involves several steps, including setting up an IBM Cloud account, creating a Speech to Text service, and integrating the service into your application.

Step 1: Set up an IBM Cloud account

If you don't have an IBM Cloud account, sign up for a free account at https://cloud.ibm.com/registration.

Step 2: Install the IBM Watson SDK

Open your terminal or command prompt and install the IBM Watson SDK for Python:

pip install ibm-watson

Step 3: Create a Speech to Text service

Once you have an IBM Cloud account, log in, and create a new Speech to Text service instance:

• Go to https://cloud.ibm.com/catalog/services/speech-to-text and click on "Create" to create a new Speech to Text service.
• Choose a plan (Lite plan should be sufficient for testing and small-scale usage).
• Give your service a name and click on "Create."

Step 4: Obtain the API key and URL

After creating the Speech to Text service instance, you need to obtain the API key and URL, which will be used to authenticate your requests:

• Go to the "Manage" section of your Speech to Text service instance.
• Click on "Show Credentials" to reveal your API key and URL.

Step 5: Write the Python code

Now, let's create a Python script to use the Watson Speech to Text service:

from ibm_watson import SpeechToTextV1
from ibm_watson.websocket import RecognizeCallback, AudioSource
from ibm_cloud_sdk_core.authenticators import IAMAuthenticator

# Replace 'YOUR_API_KEY' and 'YOUR_URL' with the actual API key and URL obtained in Step 4
authenticator = IAMAuthenticator('YOUR_API_KEY')
speech_to_text = SpeechToTextV1(authenticator=authenticator)
speech_to_text.set_service_url('YOUR_URL')

# The audio file you want to transcribe
audio_file = 'path/to/your/audio.wav'

# Open the audio file and set the RecognizeCallback
class MyRecognizeCallback(RecognizeCallback):
    def __init__(self):
        RecognizeCallback.__init__(self)

    def on_transcription(self, transcript):
        print(transcript)

    def on_connected(self):
        print('Connection was successful')

    def on_error(self, error):
        print('Error received: {}'.format(error))

    def on_inactivity_timeout(self, error):
        print('Inactivity timeout: {}'.format(error))

# Open the audio file and start the transcription
with open(audio_file, 'rb') as audio_file:
    audio_source = AudioSource(audio_file)
    callback = MyRecognizeCallback()
    speech_to_text.recognize_using_websocket(audio=audio_source, content_type='audio/wav', recognize_callback=callback)

Replace 'path/to/your/audio.wav' with the path to your audio file that you want to transcribe. Ensure the audio file is in WAV format, as the example above uses the 'audio/wav' content type.

Step 6: Run the Python script

Save the Python code to a file (e.g., speech_to_text_example.py) and run it using the command:

python speech_to_text_example.py

The script will transcribe the audio and print the results to the console.

That's it! You've now implemented IBM Watson Speech to Text using Python.