EDBT 2026 Demo / reviewers in the wild / expert
Joan Bachenko
dblp:24/5885
· DBLP profile ↗
7ranked-venue papers
5as first author
0since 2021 · last 2008
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 7 · 5 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2 · 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.
| Artificial intelligence
1 paper |
Speech recognition and synthesis · 87% Information extraction and text analysis · 13% | |
| Software engineering, system software, and programming languages
1 paper |
Compilers and program optimization · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Speech recognition and synthesis › text-to-speech synthesis
prosody modeling |
0.0 | 1 | 1986 | The Contribution of Parsing to prosodic phrasing in an Experimental Text-to-speech System · ACL 1986 |
Natural language and speech › Speech recognition and synthesis
text-to-speech synthesis |
0.0 | 1 | 1986 | The Contribution of Parsing to prosodic phrasing in an Experimental Text-to-speech System · ACL 1986 |
Compilers and program optimization › parsing
deterministic parsing |
0.0 | 1 | 1983 | Constraining a Deterministic Parser · AAAI 1983 |
Compilers and program optimization
parsing |
0.0 | 1 | 1983 | Constraining a Deterministic Parser · AAAI 1983 |
Natural language and speech › Information extraction and text analysis
syntactic parsing |
0.0 | 1 | 1986 | The Contribution of Parsing to prosodic phrasing in an Experimental Text-to-speech System · ACL 1986 |
Methods — techniques the papers use, named apart from their topics
deterministic parsing · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | Verification and Implementation of Language-Based Deception Indicators in Civil and Criminal Narratives
Joan Bachenko, Eileen Fitzpatrick, Michael Schonwetter |
COLING | 1 |
| 2003 | Designing for errors: similarities and differences of disfluency rates and prosodic characteristics across domains
Guergana K. Savova, Joan Bachenko |
INTERSPEECH | 2 |
| 2001 | Generating Training Data for Medical Dictations
Serguei V. S. Pakhomov, Michael Schonwetter, Joan Bachenko |
NAACL | 3 |
| 1995 | A rule-based phrase parser for real-time text-to-speech synthesisabstractAbstract Text-to-speech systems are currently designed to work on complete sentences and paragraphs, thereby allowing front end processors access to large amounts of linguistic context. Problems with this design arise when applications require text to be synthesized in near real time, as it is being typed. How does the system decide which incoming words should be collected and synthesized as a group when prior and subsequent word groups are unknown? We describe a rule-based parser that uses a three cell buffer and phrasing rules to identify break points for incoming text. Words up to the break point are synthesized as new text is moved into the buffer; no hierarchical structure is built beyond the lexical level. The parser was developed for use in a system that synthesizes written telecommunications by Deaf and hard of hearing people. These are texts written entirely in upper case, with little or no punctuation, and using a nonstandard variety of English (e.g.WHEN DO I WILL CALL BACK YOU). The parser performed well in a three month field trial utilizing tens of thousands of texts. Laboratory tests indicate that the parser exhibited a low error rate when compared with a human reader. Joan Bachenko, Eileen Fitzpatrick, Jeffrey Daugherty |
Nat. Lang. Eng. | 1 |
| 1990 | A Computational Grammar of Discourse-Neutral Prosodic Phrasing in English
Joan Bachenko, Eileen Fitzpatrick |
Comput. Linguistics | 1 |
| 1986 | The Contribution of Parsing to prosodic phrasing in an Experimental Text-to-speech SystemabstractWhile various aspects of syntactic structure have been shown to bear on the determination of phraselevel prosody, the text-to-speech field has lacked a robust working system to test the possible relations between syntax and prosody. We describe an implemented system which uses the deterministic parser Fidditch to create the input for a set of prosody rules. The prosody rules generate a prosody tree that specifies the location and relative strength of prosodic phrase boundaries. These specifications are converted to annotations for the Bell Labs text-to-speech system that dictate modulations in pitch and duration for the input sentence.We discuss the results of an experiment to determine the performance of our system. We are encouraged by an initial 5 percent error rate and we see the design of the parser and the modularity of the system allowing changes that will upgrade this rate. Joan Bachenko, Eileen Fitzpatrick, C. E. Wright |
ACL | 1 |
| 1983 | Constraining a Deterministic Parser
Joan Bachenko, Donald Hindle, Eileen Fitzpatrick |
AAAI | 1 |