Data Annotation is a method of data labeling available in different formats like images, text, videos and audios. The most helpful use of data labeling and annotation is creating training data for ML and AI-based models. It helps the machine models to understand the input signs and patterns clearly.
When you work or own an AI or ML-based organization, it becomes quite complex to managing bot annotation tasks and the machines. This is when you need to outsource the tasks and practically, it works well for many such organizations.
In this blog, we have discussed the types of data annotation – image, text, and audio labeling services. We have shared detailed information on audio annotation as it is one of the most evolving types currently among others. Keep reading.
Types of Data Annotation
Data annotation includes image, video, text and audio annotating or labeling. These processes label the content of the objects in images, text, video and audio, based on the content format. The results need to be highly accurate to ensure the machine understands it through improved computer vision.
A process that involves annotation of different images using bounding box, semantic segmentation, polygon annotation, landmark annotation and 3D point cloud annotation techniques. There are different types of tools or software available to annotate images and the data with accuracy. A reliable team of image annotators will make use of the right technique and tools based on your requirements.
It is a practice of labeling or adding notes to a text. It can be in the form of comments, highlights, underlining, tags, links and footnotes. Generally, text annotation included notes written for the private purpose of a reader and the collaborative writing, editing, commenting, social sharing and reading. However, over the decade, machines are also fed with texts as input and those need annotation and labeling.
Audio annotation is used to make sound or speech comprehensible and recognizable to the bots like chatbot and virtual assistance through machine learning. It is done for various types of speech, a sound that is audible and to utilize it for the NLP. There are companies providing audio labeling services with the best accuracy and on-time results for each audio files.
There are different method included in the audio annotation:
Speech annotation for ML NLP
This method is annotating sound with different kinds of sentences or words while considering the spoken words and meaning of the sentences. Annotators work on recognizing the speech and listen to it carefully to annotate using additional metadata for highlighting a sentence or identify the types of speech included. The entire process is manual and demands extra care to yield accurate results when it is to be used for training the NLU or NLP based ML models.
Linguistic annotation and audio labeling
The method involves audio labeling and also helping the machine to understand and process the audio sound for training AI models. You can get in touch with one of the leading audio annotation company working with highly experienced and well-trained annotators, who are able to annotate audio files with precision.
Sound annotation for speech recognition
Sound of traffic, human conversation, vehicle movement and various other natural or unnatural sounds can also be made recognizable to the machine through this process. If you want to create such training datasets of annotated sound for speech recognition, look for high-quality audio annotation services.
In a Nutshell
Data annotation is applicable in a wide range of fields that involve AI and ML based operations. Be it image annotation, video annotation, or audio labeling services, you can find a reliable team to outsource the required task for your project.