Demo Data from SIGIR 2026 / reviewers in the wild / expert
Krist Roginski
dblp:83/1722
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 1992
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3Graphics, computer vision, multimedia, augmented reality and games · 2
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.
| Artificial intelligence
1 paper |
Speech recognition and synthesis · 100% | |
| Computer graphics and multimedia
1 paper |
Audio and music processing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Speech recognition and synthesis
alphabet recognition |
0.0 | 1 | 1991 | English Alphabet Recognition with Telephone Speech · NIPS 1991 |
Audio and music processing
speech processing |
0.0 | 1 | 1991 | English Alphabet Recognition with Telephone Speech · NIPS 1991 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1992 | A telephone speech database of spelled and spoken namesabstractThis report describes a telephone speech corpus collected at the Oregon Graduate Institute's Center for Spoken Language Understanding. Over four thousand people called in response to public requests. They were prompted by a recorded voice to say and spell their first and last names---with and without pauses, to say what city they grew up in and what city they were calling from, and to answer two yes/no questions. In order to collect sufficient instances of each letter, about 1000 callers also recited the alphabet. Each call is checked and transcribed by two people. In addition, a subset of the calls is being phonetically labeled. INTRODUCTION A successful telephone speech recognition system must deal with variations among speakers, telephone handsets, and channel characteristics. Modeling these sources of variability requires a corpus of speech samples provided by many speakers calling from different locations using different telephones. We describe the status of a telephone speech c... Ronald A. Cole, Krist Roginski, Mark A. Fanty |
ICSLP | 2 |
| 1991 | English alphabet recognition with telephone speech
Ronald A. Cole, Krist Roginski, Mark A. Fanty |
EUROSPEECH | 2 |
| 1991 | English Alphabet Recognition with Telephone Speech
Mark A. Fanty, Ronald A. Cole, Krist Roginski |
NIPS | 3 |