R is one of the most widely used languages preferred by data scientists, statisticians, and developers, which is used for statistical computing. According to one report, only Python ranks above R as the most preferred programming language amongst statisticians, developers, and data scientists.
Just like Python, the R language is preferred by data scientists and developers for ease of use, security, and comprehensive packages. If you are looking to use R for Natural Language Processing applications, below are some of the best NLP packages you must know.
1| koRpus – Top Natural Language Processing in R Package
If you are looking to analyze text, koRpus is definitely one of the best R packages that include a wide-ranging collection of functions that helps in the auto-detection of language. koRpus also consists of the indices of lexical diversity and offers R GUI plugin and IDE RKWard, which provides graphical dialogs to its essential features.
2| lsa – Natural Language Processing in R
lsa of Latent Semantic Analysis is another excellent R package for NLP application that assists in performing Latent Semantic Analysis. The basic working principle of the package is that the text has a higher latent semantic structure (lsa) concealed within the words by using Synonyms or Polysemy.
3| OpenNLP – OpenSource Natural Language Processing in R
OpenNLP offers support for various NLP tasks, including sentence segmentation, chunking, tokenization, parts-of-speech tagging, conference resolution, parsing, and named entity extraction. It also offers the R interface for Apache OpenNLP.
Quanteda is a comprehensive, fast, and customizable R package for text analysis and management. It offers a detailed framework for quantitative text analysis and provides
- support for corpus management,
- exploring keywords in context,
- generating and handling tokens,
- creating and controlling sparse matrices, and
RWeka is a comprehensive R package exclusively for data mining tasks. The package is written in Java and is a collection of multiple machine learning algorithms. RWeka contains various features for data visualization, pre-processing, classification, clustering, association rules, and more. RWeka also includes an interface code, “Weka jar,” which is located in another package called “RWekajars.”
Converse Smartly®- Speech to Text Software – Making Conversations more Intelligible!
Converse Smartly® by Folio3 is one of the most robust and precise speech-to-text software that quickly converts audio to text. Converse Smartly® assists companies and individuals to increase productivity and efficiency of business processes. One advanced feature offered by Converse Smartly® includes speech analysis, which helps businesses record and converts speech from team meetings, conferences, interviews, and seminars.
Converse Smartly® uses cutting-edge speech recognition technology to ensure the highest accuracy and preciseness technology can achieve today. The application comes with various built-in tools that enhance efficiency, comfort, and productivity for businesses to further improve its utility.
Converse Smartly® – The Technology!
Converse Smartly® is built by Folio3 as an in-house project. The application was developed to reinforce the capabilities and skillset of Folio3’s development team, which comprises leading experts from the fields of machine learning and natural language processing.
Some of the features offered by Converse Smartly® includes:
– Speech Analysis
Converse Smartly® uses advanced NLP and machine learning algorithms to recognize, analyze, and understand people’s speech patterns. The application doesn’t only perform speech recognition; instead, it is also able to understand the speech context accurately, resulting in higher accuracy.
– Text Analysis
Converse Smartly® offers text analysis using advanced techniques and approaches that enable the use of textual content as data, which subsequently can be mined for trend or pattern analysis.
– Multiple Speaker Detection
One of the most advanced features of Converse Smartly® is Speaker diarization. This feature helps with speech-to-text conversion in audios with multiple speakers through the process of partitioning input audio into homogeneous segments; with respect to the speakers.
– Live Audio Transcription
Live audio transcription enables users to convert speech to text in real-time. This is a high-utility feature that is widely used for subtitles for videos and audios.