#IBM SPEECH TO TEXT HOW TO#
#IBM SPEECH TO TEXT CODE#
#IBM SPEECH TO TEXT PASSWORD#

#IBM SPEECH TO TEXT PASSWORD#

def transcribe_audio(path_to_audio_file): username = os.environ.get(“BLUEMIX_USERNAME”) password = os.environ.get(“BLUEMIX_PASSWORD”) speech_to_text = SpeechToText(username=username, password=password) with open(join(dirname(_file_), path_to_audio_file), ‘rb’) as audio_file: return speech_to_text.recognize(audio_file, content_type=’audio/wav’)

#IBM SPEECH TO TEXT CODE#

Notice how we can do this with simply one line of code using the Python SDK. wav file to your Watson Speech to Text API and gets back the transcribed text. recorder = Recorder(“speech.wav”) recorder.record_to_file() Of course you can change “speech.wav” to be a path pointing to wherever you’d like. Record_to_file(“speech.wav”) saves your voice into speech.wav in the same folder as run.py. Record_to_file(), transcribe_audio(), and get_text_sentiment() will accomplish these tasks.

Get the sentiment score of the transcribed text via Watson AlchemyLanguage.

Transcribe the audio file into text via Watson Speech to Text service.

from speech_sentiment_python.recorder import RecorderĪt this point, we basically need to performs three tasks in this order: I’ll not go into the specific of how it works in this post but the code is very understandable. Recorder is a module built on PyAudio that’ll record your voice into a. import os import json from os.path import join, dirname from dotenv import load_dotenv from watson_developer_cloud import SpeechToTextV1 as SpeechToText from watson_developer_cloud import AlchemyLanguageV1 as AlchemyLanguage Notice dotenv and watson_developer_cloud. Once you have the Cloud Foundry CLI, use it to login to Bluemix.īut running a script is boring, let’s actually understand what’s going on in run.py.įirst, we import the necessary libraries. In case you’re wondering, the Cloud Foundry CLI is simply a command line interface that lets you talk with Bluemix directly. You can find installation instructions at the repository’s d ownload section. My preferred way of doing this is through the Cloud Foundry CLI. Next, you need to create a Speech to Text service on Bluemix. Step 2: Create the Watson Speech to Text Service

#IBM SPEECH TO TEXT HOW TO#

If you’d like to get a quick tutorial on how to get a simple web application running on Bluemix, check this out. Either way, go ahead and sign up for a Bluemix account to get your credentials.

However, the Bluemix platform does give you a very easy way to integrate your deployed apps with all your Watson services. You can use all the Watson services via our RESTful API. If you prefer deploying your applications somewhere else, that’s not a problem. Bluemix is IBM’s PaaS offering that let’s you deploy and manage your cloud applications. In order to use the the Watson services, you need to create the services and its credentials on IBM Bluemix. Watson Developer Cloud Python SDK (Step 5)īefore we start coding, let’s get the credentials squared away.Watson AlchemyLanguage and its credentials (Step 4).Watson Speech to Text Service and its credentials (Step 2 and Step 3).IBM Bluemix account for Watson API credentials (Step 1).Python (both 2.7 and 3.x will work) development environment.The capabilities and usage remain very similar. With that said, if you still prefer to go straight to the code, it’s here.įor more of a step-by-step tutorial, read on! Edit: Watson AlchemyLanguage has since been replaced by Natural Language Understanding. Since the intended audience for this tutorial is developers, I’ll be showing as much code as possible. The rest of this post will walk you through how I combined Watson’s Speech to Text and AlchemyLanguage using Python. Naturally, I jumped at the opportunity to build something on top of them. Soon after joining IBM Watson, I was excited to find out that Watson Developer Cloud offers both of these services. For this very reason, speech recognition and sentiment analysis are two of my favorite machine learning capabilities. When a machine understands speech and emotion, its interaction with us becomes more human. Speech and emotion are building blocks of how we relate to each other.

Ibm speech to text