Recognition of the Electrolaryngeal Speech: Comparison Between Human and Machine

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43932643" target="_blank" >RIV/49777513:23520/17:43932643 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-64206-2_57" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-64206-2_57</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-64206-2_57" target="_blank" >10.1007/978-3-319-64206-2_57</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Recognition of the Electrolaryngeal Speech: Comparison Between Human and Machine

Popis výsledku v původním jazyce

Automatic recognition of an electrolaryngeal speech is usually a hard task due to the fact that all phonemes tend to be voiced. However, using a strong language model (LM) for continuous speech recognition task, we can achieve satisfactory recognition accuracy. On the other hand, the recognition of isolated words or phrase sentences containing only several words poses a problem, as in this case, the LM does not have a chance to properly support the recognition. At the same time, the recognition of short phrases has a great practical potential. In this paper, we would like to discuss poor performance of the electrolaryngeal speech automatic speech recognition (ASR), especially for isolated words. By comparing the results achieved by humans and the ASR system, we will attempt to show that even humans are unable to distinguish the identity of the word, differing only in voicing, always correctly. We describe three experiments: the one represents blind recognition, i.e., the ability to correctly recognize an isolated word selected from a vocabulary of more than a million words. The second experiment shows results achieved when there is some additional knowledge about the task, specifically, when the recognition vocabulary is reduced only to words that actually are included in the test. And the third test evaluates the ability to distinguish two similar words (differing only in voicing) for both the human and the ASR system.

Název v anglickém jazyce

Recognition of the Electrolaryngeal Speech: Comparison Between Human and Machine

Popis výsledku anglicky

Automatic recognition of an electrolaryngeal speech is usually a hard task due to the fact that all phonemes tend to be voiced. However, using a strong language model (LM) for continuous speech recognition task, we can achieve satisfactory recognition accuracy. On the other hand, the recognition of isolated words or phrase sentences containing only several words poses a problem, as in this case, the LM does not have a chance to properly support the recognition. At the same time, the recognition of short phrases has a great practical potential. In this paper, we would like to discuss poor performance of the electrolaryngeal speech automatic speech recognition (ASR), especially for isolated words. By comparing the results achieved by humans and the ASR system, we will attempt to show that even humans are unable to distinguish the identity of the word, differing only in voicing, always correctly. We describe three experiments: the one represents blind recognition, i.e., the ability to correctly recognize an isolated word selected from a vocabulary of more than a million words. The second experiment shows results achieved when there is some additional knowledge about the task, specifically, when the recognition vocabulary is reduced only to words that actually are included in the test. And the third test evaluates the ability to distinguish two similar words (differing only in voicing) for both the human and the ASR system.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/LO1506" target="_blank" >LO1506: Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnost</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

Text, Speech and Dialogue, 20th International Conference, TSD 2017, Prague, Czech Republic, August 27-31 August, 2017, Proceedings

ISBN

978-3-319-64205-5

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

9

Strana od-do

509-517

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Prague, Czech Republic

Datum konání akce

27. 8. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000449869200057