speech-to-text.md

Hints for Speech-to-Text challenge

Create a new Python 3.6 Notebook in Azure Notebooks. Next, create a Speech API Key in the Azure Portal:

As region, we'll be using West Europe in this example. You can find your API key under the service, then Keys.

You can use this file test.wav for testing.

Speech-to-Text

First, we need to request a token from the Issue Token endpoint of the Speech API. Each token is valid for 10 minutes, hence we can either reuse it multiple times (to minimize network traffic and latency), or request a new one for each call:

import requests, json

api_key = "xxx" # Enter your API key here

token_url = "https://westeurope.api.cognitive.microsoft.com/sts/v1.0/issuetoken"
headers = {'Ocp-Apim-Subscription-Key': api_key}

response = requests.post(token_url, headers=headers)
token = response.text

print("Token: " + token)

Now that we have a token, we can call the speech-to-text endpoint and include the wav data

url = "https://westeurope.stt.speech.microsoft.com/speech/recognition/conversation/cognitiveservices/v1"

headers = {'Authorization': 'Bearer ' + token,
           'Accept': 'application/json',
           'Ocp-Apim-Subscription-Key': api_key,
           'Content-Type': 'audio/wav; codec=audio/pcm; samplerate=16000'}

params = {'language': 'en-US', 'format': 'detailed'}

with open("test.wav", 'rb') as f:
    data = f.read()

response = requests.post(url, headers=headers, params=params, data=data)
print(json.dumps(response.json(), indent=2))

For recognizing longer text with multiple sentences, you can follow the following tutorial.

Note:

As of May 2019, also compressed audio is supported (e.g., MP3s), see here,

Besides that, the speech-to-text API expects audio with the following specifics:

• 16-bit WAV format with PCM or OGG format with OPUS
• Single channel (mono) at 8 or 16 KHz

More details, see here.