Research toward mechanical recognition of speech is laying the foundation for significant advances in pattern recognition and artificial intelligence This paper explains the nature of some of these advances and provides an introduction to the state of the art of automatic speech recognition

Speech Recognition: A Tutorial Overview

We are interested in determining whether the given utterance comes from a member of a given speaker group or an imposter If it is the former, we are interested in determining the identity of the speaker The only knowledge available is a set of known utterances from the given group of speakers The given utterance is manually divided into phonemes without necessarily ascertaining the identity of phonemes Using statistical decision theory, we will develop various types of tests for speaker verification and identification using only one phoneme segment or the entire utterance We will consider related problems such as the methods of clustering speakers to aid speaker verification, the optimal choice of phonemes for speaker recognition Next we consider the role of speaker variability in speech recognition and recognize its complementarity to the problem of optimal choice of phonemes for speaker recognition We illustrate the efficacy of the various methods developed here by considering the speaker and speech identification problems with three speech data bases

http://ieeexplore.ieee.org/iel6/29/26121/01162860.pdf

Speaker recognition from an unknown utterance and speaker-speech interaction

We are interested in determining whether the given utterance comes from a member of a given speaker group or an imposter. If it is the former, we are interested in determining the identity of the speaker. The only knowledge available is a set of known utterances from the given group of speakers. The given utterance is manually divided into phonemes without necessarily ascertaining the identity of phonemes. Using statistical decision theory, we will develop various types of tests for speaker verification and identification using only one phoneme segment or the entire utterance. We will consider related problems such as the methods of clustering speakers to aid speaker verification, the optimal choice of phonemes for speaker recognition. Next we consider the role of speaker variability in speech recognition and recognize its complementarity to the problem of optimal choice of phonemes for speaker recognition. We illustrate the efficacy of the various methods developed here by considering the speaker and speech identification problems with three speech data bases.

A tree-search algorithm was utilized in decoding the noisy phonetic output of an acoustic processor (AP) for purposes of automatic recognition of continuous speech. A 250-word lexicon and a finite-state grammar specify the tree to be searched. The search is performed in a best-first manner where partial paths having the highest similarity measure are extended first. The similarity measure of a word represents the degree of match of the noisy input with the best-fitting phonetic variant of that word. Phonetic variants for each word are generated automatically by a set of phonological rules. Computation of the similarity measure is based on statistics characterizing the performance of the AP. These statistics were obtained from training data by an iterative procedure. Performance results are given for both training and test data. Substantial improvement over earlier performance on the same data was realized.

http://ieeexplore.ieee.org/iel6/29/26109/01162636.pdf

Experiments with a tree-search method for converting noisy phonetic representation into standard orthography

The main purpose of this paper is to explore the significance of identity and access management systems in different businesses. The IAM system typically consists of specified functions as an information security system. The essential role is authentication because it is capable of providing confirmation of user identification for service providers utilizing IAM. The purpose of this article is to offer a review of intelligent authentication studies with regard to IAM systems. These studies are assessed in light of the proposed crucial components for intelligent authentication. According to the findings of this study, it's not possible to develop and deploy an authentication system that met all of the conditions. To manage modern multifaceted IT environments, it is essential for users to have access to every application, system software, databases platform and so on with distinct identity and related responsibilities. This method requires users to remember many passwords and IT personnel to repeat work for each platform to provide and maintain users. This affects productivity and raises the danger of the user being able to access important data and other business resources inappropriately. An alternative is a comprehensive and smart solution to Identity and Access Management (IAM) integrated with artificial intelligence. Companies have been able to condense the many identities of each user into a couple or, preferably, one identity and establish a single set of responsibilities, rules, processes, and proof of that identity. This method substantially automates IAM utilizing artificial intelligence, which enhances user and IT efficiency and optimizes safety and compliance. This paper demonstrates how the intelligent IAM interacts with artificial intelligence to streamlines many important tasks such as identity management and user authentication.

The Interaction Between Artificial Intelligence and Identity & Access Management: An Empirical study

A procedure for adaptive control of the interaction between acoustic classification and linguistic decoding in automatic recognition of continuous speech

An adaptive-control procedure is described which is intended to improve both acoustic analysis and linguistic decoding in automatic recognition of continuous speech by bringing into agreement data available at each of these stages. Specifically, hypotheses are formed by the decoder concerning the phonetic transcription derived during acoustic analysis. The procedure then accesses and utilizes relevant acoustic data in an attempt to verify or reject these hypotheses. Depending on the success of such attempts, actions are taken to constrain the decoding in subsequent processing iterations. Preliminary results are presented and discussed.

/pdf/a-procedure-for-adaptive-control-of-the-interaction-between-41o8pnfam0.pdf

N. R. Dixon

Papers

A procedure for adaptive control of the interaction between acoustic classification and linguistic decoding in automatic recognition of continuous speech

A procedure for adaptive control of the interaction between acoustic classification and linguistic decoding in automatic recognition of continuous speech