Boosting of Contextual Information in ASR for Air-Traffic Call-Sign Recognition

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F21%3APU142968" target="_blank" >RIV/00216305:26230/21:PU142968 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.isca-speech.org/archive/interspeech_2021/kocour21_interspeech.html" target="_blank" >https://www.isca-speech.org/archive/interspeech_2021/kocour21_interspeech.html</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.21437/Interspeech.2021-1619" target="_blank" >10.21437/Interspeech.2021-1619</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Boosting of Contextual Information in ASR for Air-Traffic Call-Sign Recognition

Popis výsledku v původním jazyce

Contextual adaptation of ASR can be very beneficial for multiaccent and often noisy Air-Traffic Control (ATC) speech. Our focus is call-sign recognition, which can be used to track conversations of ATC operators with individual airplanes. We developed a two-stage boosting strategy, consisting of HCLG boosting and Lattice boosting. Both are implemented as WFST compositions and the contextual information is specific to each utterance. In HCLG boosting we give score discounts to individual words, while in Lattice boosting the score discounts are given to word sequences. The context data have origin in surveillance database of OpenSky Network. From this, we obtain lists of call-signs that are made more likely to appear in the best hypothesis of ASR. This also improves the accuracy of the NLU module that recognizes the call-signs from the best hypothesis of ASR. As part of ATCO2 project, we collected liveatc test set2. The boosting of call-signs leads to 4.7% absolute WER improvement and 27.1% absolute increase of Call-Sign recognition Accuracy (CSA). Our best result of 82.9% CSA is quite good, given that the data is noisy, and WER 28.4% is relatively high. We believe there is still room for improvement.

Název v anglickém jazyce

Boosting of Contextual Information in ASR for Air-Traffic Call-Sign Recognition

Popis výsledku anglicky

Contextual adaptation of ASR can be very beneficial for multiaccent and often noisy Air-Traffic Control (ATC) speech. Our focus is call-sign recognition, which can be used to track conversations of ATC operators with individual airplanes. We developed a two-stage boosting strategy, consisting of HCLG boosting and Lattice boosting. Both are implemented as WFST compositions and the contextual information is specific to each utterance. In HCLG boosting we give score discounts to individual words, while in Lattice boosting the score discounts are given to word sequences. The context data have origin in surveillance database of OpenSky Network. From this, we obtain lists of call-signs that are made more likely to appear in the best hypothesis of ASR. This also improves the accuracy of the NLU module that recognizes the call-signs from the best hypothesis of ASR. As part of ATCO2 project, we collected liveatc test set2. The boosting of call-signs leads to 4.7% absolute WER improvement and 27.1% absolute increase of Call-Sign recognition Accuracy (CSA). Our best result of 82.9% CSA is quite good, given that the data is noisy, and WER 28.4% is relatively high. We believe there is still room for improvement.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings Interspeech 2021

ISBN

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ISSN

1990-9772

e-ISSN

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Počet stran výsledku

5

Strana od-do

3301-3305

Název nakladatele

International Speech Communication Association

Místo vydání

Brno

Místo konání akce

Brno

Datum konání akce

30. 8. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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