Deep learningDeep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
PasswordA password, sometimes called a passcode (for example in Apple devices), is secret data, typically a string of characters, usually used to confirm a user's identity. Traditionally, passwords were expected to be memorized, but the large number of password-protected services that a typical individual accesses can make memorization of unique passwords for each service impractical. Using the terminology of the NIST Digital Identity Guidelines, the secret is held by a party called the claimant while the party verifying the identity of the claimant is called the verifier.
Password strengthPassword strength is a measure of the effectiveness of a password against guessing or brute-force attacks. In its usual form, it estimates how many trials an attacker who does not have direct access to the password would need, on average, to guess it correctly. The strength of a password is a function of length, complexity, and unpredictability. Using strong passwords lowers the overall risk of a security breach, but strong passwords do not replace the need for other effective security controls.
Password managerA password manager is a computer program that allows users to store and manage their passwords for local applications or online services such as web applications, online shops or social media. Password managers can generate passwords and fill online forms. Password managers may exist as a mix of: computer applications, mobile applications, or as web browser extensions. A password manager may assist in generating passwords, storing passwords, usually in an encrypted database.
One-time passwordA one-time password (OTP), also known as a one-time PIN, one-time authorization code (OTAC) or dynamic password, is a password that is valid for only one login session or transaction, on a computer system or other digital device. OTPs avoid several shortcomings that are associated with traditional (static) password-based authentication; a number of implementations also incorporate two-factor authentication by ensuring that the one-time password requires access to something a person has (such as a small keyring fob device with the OTP calculator built into it, or a smartcard or specific cellphone) as well as something a person knows (such as a PIN).
Password crackingIn cryptanalysis and computer security, password cracking is the process of recovering passwords from data that has been stored in or transmitted by a computer system in scrambled form. A common approach (brute-force attack) is to repeatedly try guesses for the password and to check them against an available cryptographic hash of the password. Another type of approach is password spraying, which is often automated and occurs slowly over time in order to remain undetected, using a list of common passwords.
Speaker recognitionSpeaker recognition is the identification of a person from characteristics of voices. It is used to answer the question "Who is speaking?" The term voice recognition can refer to speaker recognition or speech recognition. Speaker verification (also called speaker authentication) contrasts with identification, and speaker recognition differs from speaker diarisation (recognizing when the same speaker is speaking).
Speech synthesisSpeech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech synthesizer, and can be implemented in software or hardware products. A text-to-speech (TTS) system converts normal language text into speech; other systems render symbolic linguistic representations like phonetic transcriptions into speech. The reverse process is speech recognition. Synthesized speech can be created by concatenating pieces of recorded speech that are stored in a database.
Language modelA language model is a probabilistic model of a natural language that can generate probabilities of a series of words, based on text corpora in one or multiple languages it was trained on. Large language models, as their most advanced form, are a combination of feedforward neural networks and transformers. They have superseded recurrent neural network-based models, which had previously superseded the pure statistical models, such as word n-gram language model.
Generalized method of momentsIn econometrics and statistics, the generalized method of moments (GMM) is a generic method for estimating parameters in statistical models. Usually it is applied in the context of semiparametric models, where the parameter of interest is finite-dimensional, whereas the full shape of the data's distribution function may not be known, and therefore maximum likelihood estimation is not applicable. The method requires that a certain number of moment conditions be specified for the model.
