Some trivia about the importance of speech data annotation! |
Posted: May 5, 2018 |
Although it is a known fact that we are teaching our computers to take care of various problems like how to win a chess game or determining the shortest driving path to our desired destination. However, there are still a number of tasks that even the computers still cannot perform, particularly when it is in the realm of understanding human language. This is where speech data annotation comes into picture. A number of statistical methods have proven to be a useful to way to tackle such problems but machine language learning techniques often turn out to be effective only when the respective algorithms are provided with pointers. These pointers often come in the form of annotations or metadata that provides additional information about the text. But if you want your computer to learn effectively then it is essential that you give the right data from which it can learn. So, here in this post I will be telling you about the importance of annotation and also how you can create good data to accomplish your own machine language task. Hence, just snug up and read on. The importance of speech data annotation: We all know that the Internet is a wondrous resource for all sorts of information that can teach anyone just about anything. Be it juggling, programming, playing an instrument, and so on, the list goes on. However, apart from this, there is another layer of information which is inside the Internet. This is nothing but how all those lessons (and blogs, forums, tweets, etc.) are being communicated. Fascinating, it may seem but the Web contains information in all forms of media such as texts, images, movies, and sounds and the machine language becomes the communicating medium that allows people to understand the content and to link the content to other media. However, the computers are excellent at delivering this information to interested users; but when it comes to understanding the language itself, they are much less adept. According to experts in this field, theoretical and computational linguistics are always focused on unraveling the deeper nature of language and capturing the computational properties of linguistic structures. Now, based on this the Human language technologies (HLTs) attempt to adopt these insights and algorithms and try to make them into functioning, high-performance programs that can enhance the ways we interact with computers using a language to communicate. Since almost a billion people are using the Internet every day, the accumulated amount of linguistic data available to researchers has also increased significantly which has allowed linguistic modeling problems to be viewed as ML tasks. However, the whole job is not enough to simply provide any computer with a large amount of data and expect it to learn to speak and understand conveniently. We need to prepare the data in such a way that the computer can more easily find patterns and inferences. This is usually achieved by adding relevant metadata to a dataset. Any metadata tag used to mark up various elements of the dataset is known as an annotation over the input. However, in order for the algorithms to learn efficiently and effectively, you need to do the annotation on the data accurately which should also be relevant to the task the machine is supposed to perform. Due to this reason, the method of language annotation is a vital link in developing intelligent human language technologies. Finally, Another important fact is that datasets of natural language are referred to as corpora, and hence if a single set of data annotated with the same specification then it is called an annotated corpus. Annotated corpora are often used to train ML algorithms. It is also frequently used in the methodology used for enriching a linguistic data collection that contains annotations for machine learning. So what else would you like to know about speech data annotation? Feel free to mention them in the comments section and I will be addressing them in the future posts. Also, if you found the information helpful then do share it with your social peers and keep following this space for more related updates.
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