Speaker Classification II Selected Papers /

Speaker Classification II Selected Papers / [electronic resource] : edited by C. Müller. - 1st ed. 2007. - X, 309 p. online resource. - Lecture Notes in Artificial Intelligence, 4441 2945-9141 ; . - Lecture Notes in Artificial Intelligence, 4441 .

A Study of Acoustic Correlates of Speaker Age -- The Impact of Visual and Auditory Cues in Age Estimation -- Development of a Femininity Estimator for Voice Therapy of Gender Identity Disorder Clients -- Real-Life Emotion Recognition in Speech -- Automatic Classification of Expressiveness in Speech: A Multi-corpus Study -- Acoustic Impact on Decoding of Semantic Emotion -- Emotion from Speakers to Listeners: Perception and Prosodic Characterization of Affective Speech -- Effects of the Phonological Contents on Perceptual Speaker Identification -- Durations of Context-Dependent Phonemes: A New Feature in Speaker Verification -- Language–Independent Speaker Classification over a Far–Field Microphone -- A Linear-Scaling Approach to Speaker Variability in Poly-segmental Formant Ensembles -- Sound Change and Speaker Identity: An Acoustic Study -- Bayes-Optimal Estimation of GMM Parameters for Speaker Recognition -- Speaker Individualities in Speech Spectral Envelopes and Fundamental Frequency Contours -- Speaker Segmentation for Air Traffic Control -- Detection of Speaker Characteristics Using Voice Imitation -- Reviewing Human Language Identification -- Underpinning /nailon/: Automatic Estimation of Pitch Range and Speaker Relative Pitch -- Automatic Dialect Identification: A Study of British English -- ACCDIST: An Accent Similarity Metric for Accent Recognition and Diagnosis -- Selecting Representative Speakers for a Speech Database on the Basis of Heterogeneous Similarity Criteria -- Speaker Classification by Means of Orthographic and Broad Phonetic Transcriptions of Speech.

As well as conveying a message in words and sounds, the speech signal carries information about the speaker's own anatomy, physiology, linguistic experience and mental state. These speaker characteristics are found in speech at all levels of description: from the spectral information in the sounds to the choice of words and utterances themselves. This two volume set, LNAI 4343 and LNAI 4441, constitutes a state-of-the-art survey for the field of speaker classification. It approaches the following questions: What characteristics of the speaker become manifest in his or her voice and speaking behavior? Which of them can be inferred from analyzing the acoustic realizations? What can this information be used for? Which methods are the most suitable for diversified problems in this area of research? How should the quality of the results be evaluated? The 22 articles of the second volume comprise a number of selected self-contained papers on research projects in the field of speaker classification. These include among other things a report on a gender recognition system; a study on emotion recognition; a presentation of a text-dependent speaker verification system; an account of the analysis of both speaker and verbal content information - as well as studies on accent identification.

9783540741220

10.1007/978-3-540-74122-0 doi


Signal processing.
Pattern recognition systems.
Application software.
Artificial intelligence.
Natural language processing (Computer science).
User interfaces (Computer systems).
Human-computer interaction.
Signal, Speech and Image Processing.
Automated Pattern Recognition.
Computer and Information Systems Applications.
Artificial Intelligence.
Natural Language Processing (NLP).
User Interfaces and Human Computer Interaction.

TK5102.9

621.382
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