Recognition of the Electrolaryngeal Speech: Comparison Between Human and Machine

Result code in 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>

Result on the web

<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>

Result language

angličtina

Original language name

Recognition of the Electrolaryngeal Speech: Comparison Between Human and Machine

Original language description

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.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

20205 - Automation and control systems

Project

<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>

Continuities

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

Publication year

2017

Confidentiality

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

Article name in the collection

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

—

Number of pages

9

Pages from-to

509-517

Publisher name

Springer

Place of publication

Cham

Event location

Prague, Czech Republic

Event date

Aug 27, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000449869200057