Retrieving radio news broadcasts in Danish: accuracy and categorization of unrecognized words

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

Retrieving radio news broadcasts in Danish : accuracy and categorization of unrecognized words. / Hertzum, Morten; Lund, Haakon; Troelsgård, Rasmus.

OzCHI'16: The 28th Australian Conference on Compute-Human Interaction. New York : ACM, 2016. p. 160-164.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Hertzum, M, Lund, H & Troelsgård, R 2016, Retrieving radio news broadcasts in Danish: accuracy and categorization of unrecognized words. in OzCHI'16: The 28th Australian Conference on Compute-Human Interaction. ACM, New York, pp. 160-164, Australian Conference on Human-Computer Interaction , Australia, 29/11/2016. https://doi.org/10.1145/3010915.3010972

APA

Hertzum, M., Lund, H., & Troelsgård, R. (2016). Retrieving radio news broadcasts in Danish: accuracy and categorization of unrecognized words. In OzCHI'16: The 28th Australian Conference on Compute-Human Interaction (pp. 160-164). ACM. https://doi.org/10.1145/3010915.3010972

Vancouver

Hertzum M, Lund H, Troelsgård R. Retrieving radio news broadcasts in Danish: accuracy and categorization of unrecognized words. In OzCHI'16: The 28th Australian Conference on Compute-Human Interaction. New York: ACM. 2016. p. 160-164 https://doi.org/10.1145/3010915.3010972

Author

Hertzum, Morten ; Lund, Haakon ; Troelsgård, Rasmus. / Retrieving radio news broadcasts in Danish : accuracy and categorization of unrecognized words. OzCHI'16: The 28th Australian Conference on Compute-Human Interaction. New York : ACM, 2016. pp. 160-164

Bibtex

@inproceedings{d51a1daf83f7498aa5bb34e2dd2443c6,
title = "Retrieving radio news broadcasts in Danish: accuracy and categorization of unrecognized words",
abstract = "Digital archives of radio news broadcasts can possibly be made searchable by combining speech recognition with information retrieval. We explore this possibility for the retrieval of news broadcasts in Danish. An average of 84% of the words in the broadcasts was recognized. Most of the unrecognized words were compounds, names, and other words that appear of value to retrieval. Thus, the set of words describing a broadcast has to be expanded to compensate for the recognition errors. We discuss doing this by exploiting the alternative matches from the speech recognizer and by extracting words from a related corpus",
author = "Morten Hertzum and Haakon Lund and Rasmus Troelsg{\aa}rd",
year = "2016",
doi = "10.1145/3010915.3010972",
language = "English",
pages = "160--164",
booktitle = "OzCHI'16",
publisher = "ACM",
note = "Australian Conference on Human-Computer Interaction , OzCHI 2016 ; Conference date: 29-11-2016 Through 02-12-2016",
url = "http://www.ozchi.org/2016/index.html",

}

RIS

TY - GEN

T1 - Retrieving radio news broadcasts in Danish

T2 - Australian Conference on Human-Computer Interaction

AU - Hertzum, Morten

AU - Lund, Haakon

AU - Troelsgård, Rasmus

N1 - Conference code: 28

PY - 2016

Y1 - 2016

N2 - Digital archives of radio news broadcasts can possibly be made searchable by combining speech recognition with information retrieval. We explore this possibility for the retrieval of news broadcasts in Danish. An average of 84% of the words in the broadcasts was recognized. Most of the unrecognized words were compounds, names, and other words that appear of value to retrieval. Thus, the set of words describing a broadcast has to be expanded to compensate for the recognition errors. We discuss doing this by exploiting the alternative matches from the speech recognizer and by extracting words from a related corpus

AB - Digital archives of radio news broadcasts can possibly be made searchable by combining speech recognition with information retrieval. We explore this possibility for the retrieval of news broadcasts in Danish. An average of 84% of the words in the broadcasts was recognized. Most of the unrecognized words were compounds, names, and other words that appear of value to retrieval. Thus, the set of words describing a broadcast has to be expanded to compensate for the recognition errors. We discuss doing this by exploiting the alternative matches from the speech recognizer and by extracting words from a related corpus

U2 - 10.1145/3010915.3010972

DO - 10.1145/3010915.3010972

M3 - Article in proceedings

SP - 160

EP - 164

BT - OzCHI'16

PB - ACM

CY - New York

Y2 - 29 November 2016 through 2 December 2016

ER -

ID: 168296307