S. Austin

504 total citations
14 papers, 340 citations indexed

About

S. Austin is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, S. Austin has authored 14 papers receiving a total of 340 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 5 papers in Signal Processing and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in S. Austin's work include Speech Recognition and Synthesis (10 papers), Neural Networks and Applications (6 papers) and Natural Language Processing Techniques (5 papers). S. Austin is often cited by papers focused on Speech Recognition and Synthesis (10 papers), Neural Networks and Applications (6 papers) and Natural Language Processing Techniques (5 papers). S. Austin collaborates with scholars based in United States and United Kingdom. S. Austin's co-authors include Richard Schwartz, J. Makhoul, G. Zavaliagkos, Ján Rohlíček, Mari Ostendorf, Owen Kimball, Francis Kubala, Long Nguyen, Chris Barry and F. Fallside and has published in prestigious journals such as International Conference on Acoustics, Speech, and Signal Processing.

In The Last Decade

S. Austin

9 papers receiving 266 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
S. Austin United States	7	312	159	38	10	10	14	340
D.B. Paul United States	8	394 1.3×	247 1.6×	65 1.7×	8 0.8×	11 1.1×	12	431
Franco Mana Italy	10	369 1.2×	285 1.8×	40 1.1×	3 0.3×	9 0.9×	41	419
Kofi Boakye United States	8	204 0.7×	148 0.9×	48 1.3×	4 0.4×	13 1.3×	16	259
Carlton Downey New Zealand	6	201 0.6×	136 0.9×	19 0.5×	2 0.2×	4 0.4×	13	217
Albert Sanchís Spain	11	293 0.9×	67 0.4×	52 1.4×	3 0.3×	5 0.5×	27	327
Chorkin Chan Hong Kong	8	203 0.7×	114 0.7×	80 2.1×	5 0.5×	2 0.2×	34	285
V. Gupta Canada	9	595 1.9×	511 3.2×	66 1.7×	4 0.4×	3 0.3×	23	641
Mahsa Yarmohammadi United States	6	307 1.0×	174 1.1×	27 0.7×	2 0.2×	5 0.5×	14	334
Ziqiang Zhang China	9	159 0.5×	89 0.6×	19 0.5×	2 0.2×	4 0.4×	26	212
Terry Gleason United States	9	473 1.5×	369 2.3×	29 0.8×	2 0.2×	5 0.5×	10	493

Countries citing papers authored by S. Austin

Since Specialization

Citations

This map shows the geographic impact of S. Austin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by S. Austin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Austin more than expected).

Fields of papers citing papers by S. Austin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. Austin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by S. Austin. The network helps show where S. Austin may publish in the future.

Co-authorship network of co-authors of S. Austin

This figure shows the co-authorship network connecting the top 25 collaborators of S. Austin. A scholar is included among the top collaborators of S. Austin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with S. Austin. S. Austin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

14 of 14 papers shown

1.

Austin, S., et al.. (2005). Using hidden Markov models to define linguistic units. 11. 2239–2242.

2.

Austin, S. & F. Fallside. (2003). A unified syntax direction mechanism for automatic speech recognition systems using hidden Markov models. International Conference on Acoustics, Speech, and Signal Processing. 73. 667–670.

3.

Austin, S. & F. Fallside. (2003). Frame compression in hidden Markov models. 477–480. 3 indexed citations

4.

Austin, S., G. Zavaliagkos, J. Makhoul, & Richard Schwartz. (2003). Continuous speech recognition using segmental neural nets. 2. 314–319. 1 indexed citations

5.

Austin, S., G. Zavaliagkos, J. Makhoul, & Richard Schwartz. (2002). A hybrid continuous speech recognition system using segmental neural nets with hidden Markov models. 347–356. 1 indexed citations

6.

Austin, S., G. Zavaliagkos, J. Makhoul, & Richard Schwartz. (1992). Speech recognition using segmental neural nets. 625–628 vol.1. 23 indexed citations

7.

Schwartz, Richard, S. Austin, Francis Kubala, et al.. (1992). New uses for the N-Best sentence hypotheses within the BYBLOS speech recognition system. 33 indexed citations

8.

Austin, S., G. Zavaliagkos, J. Makhoul, & Richard Schwartz. (1992). Improving state-of-the-art continuous speech recognition systems using the N-best paradigm with neural networks. 180–180. 3 indexed citations

9.

Ostendorf, Mari, et al.. (1991). Integration of diverse recognition methodologies through reevaluation of N-best sentence hypotheses. 83–87. 75 indexed citations

10.

Austin, S., et al.. (1991). The forward-backward search algorithm. 697–700 vol. 1. 63 indexed citations

11.

Austin, S., Madeleine Bates, Robert Bobrow, et al.. (1991). BBN HARC and Delphi results on the ATIS benchmarks---February 1991. 112–115. 1 indexed citations

12.

Kubala, Francis, et al.. (1991). BYBLOS speech recognition benchmark results. 77–82. 17 indexed citations

13.

Austin, S., J. Makhoul, Richard Schwartz, & G. Zavaliagkos. (1991). Continuous speech recognition using segmental neural nets. 249–252. 12 indexed citations

14.

Schwartz, Richard & S. Austin. (1991). A comparison of several approximate algorithms for finding multiple (N-best) sentence hypotheses. 701–704 vol. 1. 108 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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