Data Mining Practical Machine Learning Tools and Techniques

Introduction 1. Woman's Place in Man's Life Cycle 2. Images of Relationship 3. Concepts of Self and Morality 4. Crisis and Transition 5. Women's Rights and Women's Judgment 6. Visions of Maturity References Index of Study Participants General Index

In a Different Voice. Psychological Theory and Women’s Development. Cambridge, MA (Harvard University Press) 1982.

コンピュータ・サイエンス : ACM computing surveys

http://cs.uef.fi/pages/tkinnu/webpage/pdf/spoofingsurvey2014_SPCOM.pdf

Spoofing and countermeasures for speaker verification

While biometric authentication has advanced significantly in recent years, evidence shows the technology can be susceptible to malicious spoofing attacks. The research community has resp onded with dedicated countermeasures which aim to detect and deflect such attacks. Even if the literature shows that they can be effective, the problem is far from being solved; biometric systems remain vulnerable to spoofing. Despite a growing momentum to develo p spoofing countermeasures for automatic speaker verificati on, now that the technology has matured suffi ciently to support mass deployment in an array of diverse applications, greater effort will be needed in the future to ensure adequate protection against spoofing. This article provides a survey of past work and ide ntifies priority research directions for the future. We summarise previous studies involving impersonation, replay, speech synthesis and voice conversion spoofing attacks and more recent e fforts to develop dedicated countermeasures. The survey shows that future research should address the lack of standard datasets and the over-fitting of existing countermeasures to specific, know n spoofing attacks.

http://www.cs.joensuu.fi/pages/tkinnu/webpage/pdf/spoofingsurvey2014_SPCOM.pdf

Spoofing and countermeasures for speaker verification: a sur vey

Comunicacio presentada a: 8th Annual Conference of the International Speech Communication Association a Antwerp (Belgium) celebrada del 27 al 31 d'agost de 2007.

/pdf/jitter-and-shimmer-measurements-for-speaker-recognition-2ddu2skjtc.pdf

Jitter and shimmer measurements for speaker recognition

Jitter and shimmer are measures of the fundamental frequency and amplitude cycle-to-cycle variations, respectively. Both features have been largely used for the description of pathological voices, and since they characterise some aspects concerning particular voices, they are expected to have a certain degree of speaker specificity. In the current work, jitter and shimmer are successfully used in a speaker verification experiment. Moreover, both measures are combined with spectral and prosodic features using several types of normalisation and fusion techniques in order to obtain better verification results. The overall speaker verification system is also improved by using histogram equalisation as a normalisation technique previous to fusing the features by support vector machines.

/pdf/using-jitter-and-shimmer-in-speaker-verification-x6joy6413s.pdf

Using jitter and shimmer in speaker verification

Machine translation evaluation methods
are highly necessary in order to analyze the
performance of translation systems. Up to
now, the most traditional methods are the
use of automatic measures such as BLEU
or the quality perception performed by native
human evaluations. In order to complement
these traditional procedures, the
current paper presents a new human evaluation
based on the expert knowledge about
the errors encountered at several linguistic
levels: orthographic, morphological, lexical,
semantic and syntactic. The results obtained
in these experiments show that some
linguistic errors could have more influence
than other at the time of performing a perceptual evaluation.

/pdf/linguistic-based-evaluation-criteria-to-identify-statistical-267hwv5vbi.pdf

Linguistic-based evaluation criteria to identify statistical machine translation errors

Machine translation systems can be classified into rule-based and corpus-based approaches, in terms of their core methodology. Since both paradigms have been largely used during the last years, one of the aims in the research community is to know how these systems differ in terms of translation quality. To this end, this paper reports a study and comparison of several specific Catalan-Spanish machine translation systems: two rule-based and two corpus-based (particularly, statistical-based) systems, all of them freely available on the web. The translation quality analysis is performed under two different domains: journalistic and medical. The systems are evaluated by using standard automatic measures, as well as by native human evaluators. In addition to these traditional evaluation procedures, this paper reports a novel linguistic evaluation, which provides information about the errors encountered at the orthographic, morphological, lexical, semantic and syntactic levels. Results show that while rule-based systems provide a better performance at orthographic and morphological levels, statistical systems tend to commit less semantic errors. Furthermore, results show all the evaluations performed are characterised by some degree of correlation, and human evaluators tend to be specially critical with semantic and syntactic errors.

/pdf/study-and-comparison-of-rule-based-and-statistical-catalan-1yxy5t9j3x.pdf

Study and comparison of rule-based and statistical catalan-spanish machine translation systems

Voices can be deliberately disguised by means of human imitation or voice conversion. The question arises as to what extent they can be modified by using either of both methods. In the current paper, a set of speaker identification experiments are conducted; first, analysing some prosodic features extracted from voices of professional impersonators attempting to mimic a target voice and, second, using both intragender and crossgender converted voices in a spectral-based speaker recognition system. The results obtained in the current experiments show that the identification error rate increases when testing with imitated voices, as well as when using converted voices, especially the crossgender ones.

/pdf/automatic-speaker-recognition-as-a-measurement-of-voice-2am1r4jo3z.pdf

Mireia Farrús

Papers

Jitter and shimmer measurements for speaker recognition

Using jitter and shimmer in speaker verification

Linguistic-based evaluation criteria to identify statistical machine translation errors

Study and comparison of rule-based and statistical catalan-spanish machine translation systems

Automatic speaker recognition as a measurement of voice imitation and conversion