NLP Services To Make Language Readable For AI & ML Models
Text data, especially unstructured texts, is a treasure trove of useful information if properly harnessed and processed. NLP services provide a solution to this need by providing training data to create sophisticated text and speech analytics tools capable of understanding and comprehending human languages and dialects to gain useful insight from audio and text data.
What Is Natural Language Processing?
Natural Language Processing (NLP) is a sub-field of Artificial Intelligence (AI) that deals with how computers interact with natural human language. In particular, NLP uses computer algorithms to process, analyze and understand human language, including contextual nuances within written and spoken text. The technology can then be used to extract useful information or insight by analyzing vast volumes of text documents.
NLP For Chatbot Training
Chatbots are becoming a common phenomenon in the field of customer support. To perform their function, chatbots must adequately analyze the customer query, understand the intent and provide an appropriate response. That is achieved using advanced NLP machine learning algorithms, which are trained to analyze and understand natural language input from customers and match that with proper use cases, supported actions, or responses available, mimicking a natural conversation.
Text Analysis
Natural language processing is an important component in text mining, also called text analysis. Through NLP, computer algorithms are trained to “read” a piece of text as a human would do and understand the contents, contexts, and other associated nuances. With NLP, machines are also trained to transform unstructured text in databases and documents into structured data that is normalized for analysis. That is useful for businesses as it allows them to obtain insights quickly from vast amounts of data such as emails or social media posts.
Speech analysis
Speech analysis uses computer algorithms to identify human voices in speech. However, these speech analysis tools must first be trained to recognize and understand natural language. As NLP is involved in training machines to understand both spoken and written text, it is a natural part of any speech analysis project. Advanced NLP AI algorithms drive all speech recognition applications, chatboxes, and virtual assistants, such as Alexa from Amazon or Siri from Apple.
Multiple Speaker Detection
When listening to audio clips or speech and multiple people are talking, it is possible to extract the voice or audio of a specific person. Also, when a conversion has multiple speakers, it can extract only parts from a specific individual. That is possible with NLP AI algorithms trained to recognize the different voices in audio. These algorithms are trained to analyze and understand each speech audio’s different contents and contexts. That means that the AI algorithms can distinguish different speakers in a conversation.
Live Audio Transcription
In media such as TV and radio, people talk more than they type. Similarly, on some social media platforms, such as Yelp, TikTok, and Twitch, content is based more on audio than text. Voice recognition systems help monitor the live audio or help with readability. However, these voice recognition systems must first be trained to understand and process natural human language. That includes training AI algorithms to understand audio and transform it into text. In addition, these algorithms are trained in speech emotion recognition to correctly assess human speech for any emotions and reproduce them accurately in text.
Intent Classification
Intent recognition, also called intent classification, involves analyzing text data and expressions, understanding their meaning and context, and associating them with specific intent. Achieving this calls for machines to be able to process and interpret natural language correctly. That is achieved by training Al algorithms through NLP to take written or spoken speech as an input query, process and understand it and then associate the derived meaning to the target class of intent. Intent recognition is among the most widely used NLP techniques, especially in business, to analyze customers intent.
Your go-to solution for Natural Language Processing Services
At Annotation Box, we help our clients build and scale their NLP AI algorithms. Our experienced team of natural language annotators is ready to provide high-quality training data tailored to your project’s needs. Our natural language processing services provide our clients with an easy-to-use solution for sophisticated speech and text analytics needs.
Global Presence
We have experts from around the world, placing us in a unique position to understand different meanings of words in different cultures and contexts. That allows our team of experts to be dynamic and effectively handle client NLP projects with expertise.
Industry-specific solutions
At Annotation Box, we provide top-of-the-line NLP services that suit the needs of your project. Our expert annotators will work on your raw data from any industry and deliver high-quality training datasets that fit your project’s requirements.
95% Accuracy
Our expert team is highly trained, experienced, and committed to delivering high-quality text annotations. We are committed to delivering training data with an accuracy of at least 95% to achieve the success of your project.
Why Choose Us?
At Annotation Box, we maintain the highest regard for clients’ goals and dreams in any project. We strive to deliver high-quality annotation services, offering technical help where necessary and providing a conducive team environment to achieve the project objectives.
1000+
Trained Experts
95%+
Accuracy
50+
Happy Clients
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Successful Projects
Learn How We Can Help You Train Your AI & ML Models With Our Professional NLP Solutions
Our natural language processing services at Annotation Box enable you to analyze and derive useful insight from unstructured data in real time. With our professional NLP solutions, we ensure that building or scaling AI & ML models for simple or complex speech and text understanding is quick, efficient, and cost-effective. Contact one of our experts to get started.
How We Work
Get your data annotated in just 5 simple steps.
STEP : 1
Project Assessment
Upon receiving the inquiry we assign experts to understand your project requirements. After in-depth research by our experts and assessing your requirements, we deploy the best data annotation solution for you.
STEP : 2
Sample Data Labeling
After deploying data annotation solution. We begin our work. The first step is to ask for your samples. Once we receive your samples, we run sample data labeling. We label the samples and send you back for your review.
STEP : 3
Training
Once you’re satisfied with our sample. We deploy a training module for the team to impart an in-depth understanding of the project.
Our Quality analyst keeps checking for the desired quality output with our annotators.
STEP : 4
Production
Our dedicated project manager will oversee the team and monitor them constantly to ensure the annotators are meeting the desired output quality set initially and completing the project on time. Annotation Box puts accuracy first and foremost.
STEP : 5
Evaluation
We believe in transparency and high-quality data annotation. Through our continuous feedback cycle, we make sure the annotation is done correctly. Our flexible workforce enables us to scale up production at any time.
STEP : 1
Project Assessment
Upon receiving the inquiry we assign experts to understand your project requirements. After in-depth research by our experts and assessing your requirements, we deploy the best data annotation solution for you.
STEP : 2
Sample Data Labeling
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STEP : 3
Training
Once you’re satisfied with our sample. We deploy a training module for the team to impart an in-depth understanding of the project.Our Quality analyst keeps checking for the desired quality output with our annotators.
STEP : 4
Production
Our dedicated project manager will oversee the team and monitor them constantly to ensure the annotators are meeting the desired output quality set initially and completing the project on time. Annotation Box puts accuracy first and foremost.
STEP : 5
Evaluation
We believe in transparency and high-quality data annotation. Through our continuous feedback cycle, we make sure the annotation is done correctly. Our flexible workforce enables us to scale up production at any time.