Demo Data from EDBT 2026 / reviewers in the wild / expert
John J. Dubnowski
dblp:141/4124
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 1979
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 2 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
2 papers |
Audio and music processing · 100% | |
| Artificial intelligence
1 paper |
Speech recognition and synthesis · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Processor architecture and microarchitecture · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Audio and music processing
speech coding |
0.0 | 2 | 1978 | A Microprocessor Log PCM/ADPCM Code Converter · IEEE Trans. Commun. 1978 Detecting the Presence of Speech Using ADPCM Coding · IEEE Trans. Commun. 1976 |
Natural language and speech › Speech recognition and synthesis › speech analysis
voice activity detection |
0.0 | 1 | 1976 | Detecting the Presence of Speech Using ADPCM Coding · IEEE Trans. Commun. 1976 |
Audio and music processing › speech coding
adaptive differential pulse code modulation |
0.0 | 1 | 1976 | Detecting the Presence of Speech Using ADPCM Coding · IEEE Trans. Commun. 1976 |
Processor architecture and microarchitecture › microprocessor design
microprocessor implementation |
0.0 | 1 | 1978 | A Microprocessor Log PCM/ADPCM Code Converter · IEEE Trans. Commun. 1978 |
Natural language and speech › Speech recognition and synthesis › speech analysis
endpoint detection |
0.0 | 1 | 1976 | Detecting the Presence of Speech Using ADPCM Coding · IEEE Trans. Commun. 1976 |
Methods — techniques the papers use, named apart from their topics
microcoding · 0.0integrated circuit implementation · 0.0adaptive quantization · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1979 | Variable rate codingabstractIn this paper we examine a number of concepts and issues concerning variable rate coding of speech. We formulate the problem as a multistate coder (i.e. a coder that can operate at several bit rates) coupled with a time buffer. We first analyze the theoretical aspects of the problem by examining it in the context of a block processing formulation. We also allude to a multiple user configuration of variable rate coding for TASI type applications. A practical example of a variable rate ADPCM coder is presented and applied to speech coding. It is shown that by careful design the algorithm can be made to be as robust to channel errors as that of a fixed rate ADPCM coder. John J. Dubnowski, Ronald E. Crochiere |
ICASSP | 1 |
| 1978 | A Microprocessor Log PCM/ADPCM Code ConverterabstractA microprocessor has been used to translate between Log PCM and ADPCM (Adaptive Differential PCM) code forms. This system, in bridging the gap between simulation and prototyping, provides realtime speech processing with user interaction. Continuously coded speech can he subjectively evaluated while switching the values of code word length, step size, or predictor coefficients. Translations of additional code forms such as Δ-Mod, NIC, or Tree Codes could easily be implemented with the micro-codable system. The processor is configured as a stand-alone device competitive with special purpose hardware in size, speed, and cost. John J. Dubnowski |
IEEE Trans. Commun. | 1 |
| 1976 | Detecting the Presence of Speech Using ADPCM CodingabstractWhen speech is coded using a differential pulse-code modulation system with an adaptive quantizer, the digital code words exhibit considerable variation among all quantization levels during both voiced and unvoiced speech intervals. However, because of limits on the range of step sizes, during silent intervals the code words vary only slightly among the smallest quantization steps. Based on this principle, a simple algorithm for locating the beginning and end of a speech utterance has been developed. This algorithm has been tested in computer simulations and has been constructed with standard integrated circuit technology. Ronald W. Schafer, John J. Dubnowski, Lawrence R. Rabiner |
IEEE Trans. Commun. | 3 |