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Brian Kingsbury

Brian Kingsbury has 3 papers in our library, in 2017–2021, most of them on Speech & spoken language, English, Dialogue systems; often with George Saon, Michael Picheny, Zoltan Tuske.

3 papers in our library · 2017–2021

OpenAlex · ORCID · Wikidata · h-index 46 · 231 works · 22,319 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 19 times in our library · ⭐ Paper Stars ranking: #4782

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🏢IBMArmonk · United States2002–2026 · 110 paperscurrent🔬IBM Research - Thomas J. Watson Research CenterYorktown Heights · United States2002–2026 · 79 paperscurrent🎓University of California, BerkeleyBerkeley · United States1996–2003 · 8 papers🔬International Computer Science InstituteBerkeley · United States1998–2003 · 6 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 more institutions on single bylines are not listed.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksSignal Processing · 3 works

🧭 Topics 3Research subjects and languages the work is about.English · 3 worksSpeech & spoken language · 3 worksDialogue systems · 2 works

 Works by year

2020s

20211 paperOn the limit of English conversational speech recognition

2010s

20191 paperEnglish Broadcast News Speech Recognition by Humans and Machines20171 paperBuilding competitive direct acoustics-to-word models for English conversational speech recognition

 Papers

The most cited first (OpenAlex and our library).

  1. Building competitive direct acoustics-to-word models for English conversational speech recognition (2017 · 111 citations)
    Direct acoustics-to-word (A2W) models map speech straight to whole words with one neural network. They need no pronunciation lexicon, no decoder and no separately trained language model. Earlier work suggested such models need vastly more audio than phone- or character-based systems, and the authors' own previous A2W…
  2. On the limit of English conversational speech recognition (2021 · 49 citations)
    The paper asks how much further attention-based encoder-decoder ASR can be pushed on the Switchboard conversational telephone benchmark. The authors start from their earlier heavily regularized single-head LSTM encoder-decoder system. They then add several improvements:
  3. English Broadcast News Speech Recognition by Humans and Machines (2019 · 12 citations)
    The paper asks whether deep-learning recipes that brought conversational telephone speech (CTS) recognition near human level also work for English broadcast news (BN).

 Co-authors here

7 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 19 times (of the 141,840 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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