![]() Using a grammar in your “recognize” requestĪs part of each “recognize” request, you can only use one custom language model and one grammar configuration.When the training status is “available”, you are ready to use the grammar. Create a new custom model by running the “curl” command below:Ĭurl -X POST -u “apikey:".To create a Language Model Adaptation/Customization, the steps are the following: Additional emphasis can also be put on high frequency in-vocabulary words. The focus of training text data should be on ‘out-of-vocabulary’ words, and known words that the solution struggles with. Watson STT is a probabilistic and contextual service, so training can include repetitive words and phrases to ‘weight’ the chance of the word being transcribed. Out of the 3 components available for model adaptation, the Language Model Adaption is the one who delivers the biggest bang for the buck. ![]() Create a Language Model Adaptation/Customization They will indicate where Watson STT training is required and what to validate as you go through your multiple iterations. Technical terminology and jargons - product names, technical expressions, unknown domain context.Out-Of-Vocabulary words - domain-specific terms, acronyms.The obvious gaps that we usually observe at this point are: Not only you will get a Word Error Rate (WER) and a Sentence Error Rate (SER) but it will give you the areas where you need to improve. The first experiment is run against the STT Base Model with no adaptation. My friend and colleague Andrew Freed wrote a great article on how to conduct experiments for speech applications, using the sclite tool - read it for more information on experimentation. This process takes roughly the length of the. If the video is selected as being in a supported language, Watson will automatically start to caption the content through using speech to text. The first thing we must do is to set our baseline by using the Test Set we built earlier (see “Building Your Training Set and Your Test Set” in Part 1,). To convert video speech to text, content owners simply need to upload their video content to IBM’s video streaming or enterprise video streaming offerings. In order to see how Watson STT performs and how we measure improvements, we go through multiple iterations of teach, test and calibrate (ITTC).
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