![]() ![]() We can now perform synthesis of a text input and write the incoming speech stream from IBM Watson API to a file. text_to_speech = TextToSpeechV1 ( username = 'API_USERNAME ', password = 'API_PASSWORD ' ) Now we need to create a new TextToSpeechV1 object using the Service Credentials we created earlier. from watson_developer_cloud import TextToSpeechV1 It can be added using following import statement. For that, we need to first import TextToSpeechV1 library. Now we can add Text to Speech to our project. Install them using the following command. On Ubuntu with Python 3.5 watson-developer-cloud has some extra dependencies. Save it for future reference.Īfter that, we need to add Watson developer cloud python package. You will get service credentials for your newly created text to speech service. Select the standard plan from the options and then click on create button. ![]() Select Watson on the left pane and then select Text to Speech service from the list. To do so, click on Create Watson Service button We need to create a Text to Speech Service. IBM Watson TTS can be added to a Python Project easily using the IBM Watson Developer SDK.įor using the IBM Watson Developer SDK for Text to Speech, first of all, we need to sign up for BluemixĪfter that, we will get the empty dashboard without any service added currently. We, therefore, added IBM Watson Text to Speech API in SUSI Hardware project. We always crave for a more natural voice for better interaction with our assistant. While Flite is an Open Source solution that can run locally on a client, it does not provide the same quality of voice and speed as cloud providers. I previously wrote a blog on choosing a perfect Text to Speech engine for Susi AI and had used Flite as the solution for it. Susi Hardware project aims at creating a smart assistant for your home that you can run on your Raspberry Pi or similar Development Boards. ![]()
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