FAQ on Artificial Intelligence

In Artificial Intelligence, to extract the meaning from the group of sentences semantic analysis is used. Semantic analysis in artificial intelligence is used for interpreting the meaning of text or speech. It aims to understand the intended meaning of words, phrases, sentences, or entire documents within a given context. The correct answer to the question … Read more

While staying within the HMM network, the additional state variables can be added to a temporal model. In Hidden Markov Models (HMMs), the additional variable is typically added to represent the hidden states. In an HMM, you have observed data (e.g., observations or emissions) and hidden states (e.g., underlying causes or states). The additional variable … Read more

‘Possible States of the World’ is the possible values of the variable in HMM’s. In Hidden Markov Models (HMMs), there are typically three main types of variables: Observation Variables (O): These are the observable variables or emissions associated with each state in the model. They represent the data that can be directly observed. For example, … Read more

The state of the process in HMM’s model is described by a ‘Single Discrete Random Variable’. In a Hidden Markov Model (HMM), the state of the process is typically described probabilistically. Specifically, it is represented as a set of hidden states, each with associated probabilities. These hidden states represent the underlying, unobservable processes that generate … Read more

Hidden Markov Models are a ubiquitous tool for modelling time series data or to model sequence behaviour. They are used in almost all current speech recognition systems. The Hidden Markov Model (HMM) is a statistical model used in various fields including speech recognition, natural language processing, bioinformatics, and finance, among others. Here’s a concise and … Read more