Robert B. Dunn

Bio: Robert B. Dunn is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Speaker recognition & Speech coding. The author has an hindex of 15, co-authored 30 publications receiving 5320 citations. Previous affiliations of Robert B. Dunn include Alcatel-Lucent.

Scalable and embedded codec for speech and audio signals

Abstract: A system and method for processing of audio and speech signals is disclosed, which provide compatibility over a range of communication devices operating at different sampling frequencies and/or bit rates. The analyzer of the system divides the input signal in different portions, at least one of which carries information sufficient to provide intelligible reconstruction of the input signal. The analyzer also encodes separate information about other portions of the signal in an embedded manner, so that a smooth transition can be achieved from low bit-rate to high bit-rate applications. Accordingly, communication devices operating at different sampling rates and/or bit-rates can extract corresponding information from the output bit stream of the analyzer. In the present invention embedded information generally relates to separate parameters of the input signal, or to additional resolution in the transmission of original signal parameters. Non-linear techniques for enhancing the overall performance of the system are also disclosed. Also disclosed is a novel method of improving the quantization of signal parameters. In a specific embodiment the input signal is processed in two or more modes dependent on the state of the signal in a frame. When the signal is determined to be in a transition state, the encoder provides phase information about N sinusoids, which the decoder end uses to improve the quality of the output signal at low bit rates.

Fusing High- and Low-Level Features for Speaker Recognitionx

Abstract: The area of automatic speaker recognition has been dominated by systems using only short-term, low-level acoustic information, such as cepstral features. While these systems have produced low error rates, they ignore higher levels of information beyond low-level acoustics that convey speaker information. Recently published works have demonstrated that such high-level information can be used successfully in automatic speaker recognition systems by improving accuracy and potentially increasing robustness. Wide ranging high-levelfeature-based approaches using pronunciation models, prosodic dynamics, pitch gestures, phone streams, and conversational interactions were explored and developed under the SuperSID project at the 2002 JHU CLSP Summer Workshop (WS2002): http://www.clsp.jhu.edu/ws2002/groups/supersid/. In this paper, we show how these novel features and classifiers provide complementary information and can be fused together to drive down the equal error rate on the 2001 NIST Extended Data Task to 0.2%—a 71% relative reduction in error over the previous state of the art.

Speaker verification using text-constrained Gaussian Mixture Models

Abstract: In this paper we present an approach to close the gap between text-dependent and text-independent speaker verification performance. Text-constrained GMM-UBM systems are created using word segmentations produced by a LVCSR system on conversational speech allowing the system to focus on speaker differences over a constrained set of acoustic units. Results on the 2001 NIST extended data task show this approach can be used to produce an equal error rate of < 1 %.

Front-End Factor Analysis for Speaker Verification

Abstract: This paper presents an extension of our previous work which proposes a new speaker representation for speaker verification. In this modeling, a new low-dimensional speaker- and channel-dependent space is defined using a simple factor analysis. This space is named the total variability space because it models both speaker and channel variabilities. Two speaker verification systems are proposed which use this new representation. The first system is a support vector machine-based system that uses the cosine kernel to estimate the similarity between the input data. The second system directly uses the cosine similarity as the final decision score. We tested three channel compensation techniques in the total variability space, which are within-class covariance normalization (WCCN), linear discriminate analysis (LDA), and nuisance attribute projection (NAP). We found that the best results are obtained when LDA is followed by WCCN. We achieved an equal error rate (EER) of 1.12% and MinDCF of 0.0094 using the cosine distance scoring on the male English trials of the core condition of the NIST 2008 Speaker Recognition Evaluation dataset. We also obtained 4% absolute EER improvement for both-gender trials on the 10 s-10 s condition compared to the classical joint factor analysis scoring.

Distributed Systems: Principles and Paradigms

Abstract: From the Publisher: Andrew Tanenbaum and Maarten van Steen cover the principles, advanced concepts, and technologies of distributed systems in detail, including: communication, replication, fault tolerance, and security. Intended for use in a senior/graduate level distributed systems course or by professionals, this text systematically shows how distributed systems are designed and implemented in real systems. Written in the superb writing style of other Tanenbaum books, the material also features unique accessibility and a wide variety of real-world examples and case studies, such as NFS v4, CORBA, DOM, Jini, and the World Wide Web. FEATURES Detailed coverage of seven key principles. An introductory chapter followed by a chapter devoted to each key principle: communication, processes, naming, synchronization, consistency and replication, fault tolerance, and security, including unique comprehensive coverage of middleware models. Four chapters devoted to state-of-the-art real-world examples of middleware. Covers object-based systems, document-based systems, distributed file systems, and coordination-based systems including CORBA, DCOM, Globe, NFS v4, Coda, the World Wide Web, and Jini. Excellent coverage of timely, advanced, distributed systems topics: Security, payment systems, recent Internet and Web protocols, scalability, and caching and replication. NEW-The Prentice Hall Companion Website for this book contains PowerPoint slides, figures in various file formats, and other teaching aids, and a link to the author's Web site.