Data Labeling and Common Tasks

Outstanding of data labeling is a time-consuming process, as it involves human interaction for the most accurate results (Loy et al., 2020).
Let’s talk about some common tasks about Data Labeling:

POS tagging

The function of POS tagging is to identify the grammatical functions of words in a sentence. This is the basic step before in-depth analysis of grammar or other complex language processing issues.

Typically, a word can have many grammatical functions, for example:

In the sentence “con ngựa đá đá con ngựa đá “, the same word “đá” but the first and third words have grammatical functions as nouns, but the second word is a verb in the sentence.

POS tagging is considered the basis for higher semantic problems.

Named-Entity recognition

Named-Entity recognition of medium semantic value is often used to classify text. In other words, it is a data marking according to tricky tasks of machine.

For example: Ms. Ba [PERSON] sells bread [FOOD] in 13 ward [ADDRESS].

Machine translation

The method of machine translation simply means that the input is a sentence of A language, the output is the sentence of corresponding B language. MP.BPO’s able to train the analyze and recognition of Machine Learning. Moreover, we are able to Support Vector Machine (SVM) as well as other automation and fault detection.

This problem was very urgent during World War II, when enemy information needed to be translated in the shortest possible time, so that the leaders could make urgent strategies.

Speech recognition

As the name of this Labeling task, the input will be the voice sound, the output will be a text sentence. It is well-known as future technology for data visualization service. BPO.MP experts have years of experience of Data Analyze and Recognition.

Today, according to Apple statistics, users prefer to use their voice to enter text rather than traditional keyboard input, at the same time, human-machine interaction in this way has faster input speed. Therefore, it is necessary to develop and improve the output of Voice recognition and Data Digitization. For example of Home Automation, Smart Technology, Machine to Machine applications.

Although there are still certain difficulties, with increasingly advanced technology, this labeling task is gradually being improved and developed.

Conclusion

Today, with the development of digital technology, Data Labeling services become more popular and necessary.

With a wealth of experience and a large team of employees, BPO.MP is always confident of being one of the reputable outsourcing companies. Let BPO.MP take over Data Labeling tasks, contribute to the AI training of your business.

Data annotation services at BPO.MP

Data annotation plays a pivotal role in unlocking the potential of AI across industries by enabling machine learning models to learn from accurately labeled datasets. This process is key to enhancing the capabilities of systems in areas like automation, decision-making, and data-driven insights.

At BPO.MP, our Data Annotation Services focus on labeling and classifying raw data (including images, text, video, and more) to create high-quality training datasets for AI and machine learning models. These annotations are essential for businesses looking to enhance operational efficiency, drive better decision-making, and streamline processes.

From autonomous driving to healthcare and beyond, data annotation is central to AI development. Our flexible and scalable solutions at BPO.MP are designed to meet specific project requirements, ensuring precision and adaptability for any AI initiative. By leveraging our expertise, businesses can unlock the full potential of AI while optimizing workflows and reducing operational costs.