Speaker Classification Based on Multiple Criteria
Author: Miaogeng Zhang
Publisher:
Published: 2010
Total Pages: 106
ISBN-13:
DOWNLOAD EBOOKRead and Download eBook Full
Author: Miaogeng Zhang
Publisher:
Published: 2010
Total Pages: 106
ISBN-13:
DOWNLOAD EBOOKAuthor: C. Müller
Publisher: Springer Science & Business Media
Published: 2007-08-15
Total Pages: 317
ISBN-13: 3540741216
DOWNLOAD EBOOKThis two-volume set constitutes a state-of-the-art survey in the field of speaker classification, addressing many critical questions. The twenty-two articles of the second volume cover a number of areas, including gender recognition systems, emotion recognition, text-dependent speaker verification systems, an analysis of both speaker and verbal content information, and accent identification.
Author: Christian Müller
Publisher: Springer
Published: 2007-08-28
Total Pages: 363
ISBN-13: 354074200X
DOWNLOAD EBOOKThis volume and its companion volume LNAI 4441 constitute a state-of-the-art survey in the field of speaker classification. Together they address such intriguing issues as how speaker characteristics are manifested in voice and speaking behavior. The nineteen contributions in this volume are organized into topical sections covering fundamentals, characteristics, applications, methods, and evaluation.
Author: Christian Müller
Publisher: Springer Science & Business Media
Published: 2007-08-14
Total Pages: 363
ISBN-13: 3540741860
DOWNLOAD EBOOKThis volume and its companion volume LNAI 4441 constitute a state-of-the-art survey in the field of speaker classification. Together they address such intriguing issues as how speaker characteristics are manifested in voice and speaking behavior. The nineteen contributions in this volume are organized into topical sections covering fundamentals, characteristics, applications, methods, and evaluation.
Author: Homayoon Beigi
Publisher: Springer Science & Business Media
Published: 2011-12-09
Total Pages: 984
ISBN-13: 0387775927
DOWNLOAD EBOOKAn emerging technology, Speaker Recognition is becoming well-known for providing voice authentication over the telephone for helpdesks, call centres and other enterprise businesses for business process automation. "Fundamentals of Speaker Recognition" introduces Speaker Identification, Speaker Verification, Speaker (Audio Event) Classification, Speaker Detection, Speaker Tracking and more. The technical problems are rigorously defined, and a complete picture is made of the relevance of the discussed algorithms and their usage in building a comprehensive Speaker Recognition System. Designed as a textbook with examples and exercises at the end of each chapter, "Fundamentals of Speaker Recognition" is suitable for advanced-level students in computer science and engineering, concentrating on biometrics, speech recognition, pattern recognition, signal processing and, specifically, speaker recognition. It is also a valuable reference for developers of commercial technology and for speech scientists. Please click on the link under "Additional Information" to view supplemental information including the Table of Contents and Index.
Author: K. Sreenivasa Rao
Publisher: Springer
Published: 2014-06-21
Total Pages: 149
ISBN-13: 3319071300
DOWNLOAD EBOOKThis book discusses speaker recognition methods to deal with realistic variable noisy environments. The text covers authentication systems for; robust noisy background environments, functions in real time and incorporated in mobile devices. The book focuses on different approaches to enhance the accuracy of speaker recognition in presence of varying background environments. The authors examine: (a) Feature compensation using multiple background models, (b) Feature mapping using data-driven stochastic models, (c) Design of super vector- based GMM-SVM framework for robust speaker recognition, (d) Total variability modeling (i-vectors) in a discriminative framework and (e) Boosting method to fuse evidences from multiple SVM models.
Author: Partha Niyogi
Publisher:
Published: 1991
Total Pages: 214
ISBN-13:
DOWNLOAD EBOOKAuthor: Tobias Herbig
Publisher: Springer Science & Business Media
Published: 2011-06-18
Total Pages: 178
ISBN-13: 3642198996
DOWNLOAD EBOOKCurrent speech recognition systems are based on speaker independent speech models and suffer from inter-speaker variations in speech signal characteristics. This work develops an integrated approach for speech and speaker recognition in order to gain space for self-learning opportunities of the system. This work introduces a reliable speaker identification which enables the speech recognizer to create robust speaker dependent models In addition, this book gives a new approach to solve the reverse problem, how to improve speech recognition if speakers can be recognized. The speaker identification enables the speaker adaptation to adapt to different speakers which results in an optimal long-term adaptation.
Author: Arafat Abumallouh
Publisher:
Published: 2016
Total Pages: 96
ISBN-13: 9780355631753
DOWNLOAD EBOOKAbstract : Speaker age and gender classification is one of the most challenging problems in speech processing. Recently with developing technologies, identifying a speaker age and gender has become a necessity for speaker verification and identification systems such as identifying suspects in criminal cases, improving human-machine interaction, and adapting music for awaiting people queue. Although many studies have been carried out focusing on feature extraction and classifier design for improvement, classification accuracies are still not satisfactory. The key issue in identifying speaker’s age and gender is to generate robust features and to design an in-depth classifier. Age and gender information is concealed in speaker’s speech, which is liable for many factors such as, background noise, speech contents, and phonetic divergences.In this work, different methods are proposed to enhance the speaker age and gender classification based on the deep neural networks (DNNs) as a feature extractor and classifier. First, a model for generating new features from a DNN is proposed. The proposed method uses the Hidden Markov Model toolkit (HTK) tool to find tied-state triphones for all utterances, which are used as labels for the output layer in the DNN. The DNN with a bottleneck layer is trained in an unsupervised manner for calculating the initial weights between layers, then it is trained and tuned in a supervised manner to generate transformed mel-frequency cepstral coefficients (T-MFCCs). Second, the shared class labels method is introduced among misclassified classes to regularize the weights in DNN. Third, DNN-based speakers models using the SDC feature set is proposed. The speakers-aware model can capture the characteristics of the speaker age and gender more effectively than a model that represents a group of speakers. In addition, AGender-Tune system is proposed to classify the speaker age and gender by jointly fine-tuning two DNN models; the first model is pre-trained to classify the speaker age, and second model is pre-trained to classify the speaker gender. Moreover, the new T-MFCCs feature set is used as the input of a fusion model of two systems. The first system is the DNN-based class model and the second system is the DNN-based speaker model. Utilizing the T-MFCCs as input and fusing the final score with the score of a DNN-based class model enhanced the classification accuracies. Finally, the DNN-based speaker models are embedded into an AGender-Tune system to exploit the advantages of each method for a better speaker age and gender classification.The experimental results on a public challenging database showed the effectiveness of the proposed methods for enhancing the speaker age and gender classification and achieved the state of the art on this database.
Author: Phuoc Thanh Nguyen
Publisher:
Published: 2010
Total Pages: 79
ISBN-13:
DOWNLOAD EBOOKAbstract: "Gender, age, accent and emotion are some of speaker characteristics being investigated in voice-based speaker classification systems. Classifying speaker characteristics is an important task in the fields of Dialog, Speech Synthesis, Forensics, Language Learning, Assessment, and Speaker Recognition. It is well known that reducing classification error rate has been a challenge in those research fields. This research thesis investigates new methods for speech feature extraction and classification to meet this challenge."