computational linguistics
Computational linguistics is the interface between computer science and linguistics. It involves the use of computers to process natural language (both text and audio), such as speech recognition and synthesis, machine translation and dialogue systems. It is therefore an interdisciplinary field concerned with the application of computer technology to language.
One of its main goals is to enable computers to perform natural, human-like language processing, including comprehension and production. This may require hardware, such as input and output devices, as well as software programs.
The tasks of computational linguistics include the creation of language databases, the development of language processing programs and the analysis of linguistic data. The aim is to develop computer-based methods for collecting, analysing and processing large amounts of language data. It also involves the development of language models that allow the structure and meaning of language to be analysed. Language modelling helps to understand how language works and how it is used.
Applications of computational linguistics
Speech recognition systems (speech-to-text)
An important application of computational linguistics is the development of speech recognition systems. These systems are able to convert human speech into machine-readable formats. They are used to understand and interpret speech input from users. This technology is used in areas such as voice control of devices, automatic transcription of voice recordings, and the development of voice assistants.
Text-to-speech (TTS)
Text-to-speech (TTS) is a technology that converts written text into spoken words. TTS can be integrated into websites, e-books or other digital materials, for example, to enable accessibility or facilitate access to information.
TTS technology is also used in virtual assistants such as Siri, Alexa or Google Assistant, or for language translation.
Automatic translation
Another important application of computational linguistics is automated translation. Computer programs can automatically translate text from one language to another. This is used in many areas such as tourism, trade and international cooperation.
Automatic text generation
Another application of computational linguistics is automatic text generation. This involves software programmes that automatically generate texts that sound natural and contain defined content. They are used to automatically write messages, descriptions, articles and other types of text. This technology is used in marketing, advertising and news reporting (robot journalism).
Text summarisation
Automatic text summarisation is also part of computational linguistics. It automatically extracts and summarises the most important information from a text. Possible applications include content management systems (CMS) or news production. A distinction is made between extractive summarisation, which selects only the most important text components, and abstract summarisation, which also reformulates the relevant text passages and combines them into a smoothly readable text.
Text Categorisation
Another area of computational linguistics is automatic text categorisation. This is where texts are automatically categorised and sorted according to, for example, topic or style. Relevant applications include content management, news monitoring and text analysis.
Semantic analysis
Semantic analysis of text involves automatically recognising and understanding the meaning of words and phrases in a text. This is relevant, for example, for developing systems that can automatically answer questions (question answering, chatbots) or for automatically summarising text.
Sentiment analysis
Another application of computational linguistics is sentiment analysis, which detects emotions and moods. It automatically recognises whether statements are positive, negative or neutral. This technology is used to understand people’s opinions and feelings about a particular topic, product or brand. Sentiment analysis is therefore used in areas such as marketing, political analysis, social media analysis, monitoring customer feedback or identifying opinion leaders in a particular industry.
Speaker or author identification
Speaker or author identification is another use case for computational linguistics. This involves using computational methods to determine the identity of the speaker or author. This is used in forensics, social media monitoring or identity verification.
Irony and sarcasm as stylistic devices
One of the challenges in computational linguistics and automatic speech recognition is the recognition of stylistic devices such as irony, sarcasm and other linguistic nuances. This involves using computer-based methods to recognise and understand the intention behind a statement. This is important for developing systems that can automatically answer questions or analyse social media.
Chatbots
Another application of computational linguistics is the development of dialogue systems such as chatbots. These systems are able to understand human language and respond appropriately to queries. They are used to automatically perform tasks such as answering questions, carrying out transactions and providing information. This technology is used in areas such as customer service or e-commerce.
Conclusion
Computational linguistics is an interdisciplinary field that deals with the application of computer technology to language. It is used in various areas such as text and speech recognition, text and speech generation, machine translation, the development of dialogue systems, semantic analysis, the programming of chatbots and many more.
Particularly in the context of artificial intelligence, computational linguistics is a fast-growing and dynamic field, constantly producing new developments and innovations.
Sources:
https://plato.stanford.edu/entries/computational-linguistics/
https://www.techtarget.com/searchenterpriseai/definition/computational-linguistics-CL