Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F18%3APU136057" target="_blank" >RIV/00216305:26230/18:PU136057 - isvavai.cz</a>

Result on the web

<a href="https://www.isca-speech.org/archive/Interspeech_2018/abstracts/1836.html" target="_blank" >https://www.isca-speech.org/archive/Interspeech_2018/abstracts/1836.html</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.21437/Interspeech.2018-1836" target="_blank" >10.21437/Interspeech.2018-1836</a>

Result language

angličtina

Original language name

Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages

Original language description

Automatic speech recognition (ASR) systems often need to be developed for extremely low-resource languages to serve enduses such as audio content categorization and search. While universal phone recognition is natural to consider when no transcribed speech is available to train an ASR system in a language, adapting universal phone models using very small amounts (minutes rather than hours) of transcribed speech also needs to be studied, particularly with state-of-the-art DNN-based acoustic models. The DARPA LORELEI program provides a framework for such very-low-resource ASR studies, and provides an extrinsic metric for evaluating ASR performance in a humanitarian assistance, disaster relief setting. This paper presents our Kaldi-based systems for the program, which employ a universal phone modeling approach to ASR, and describes recipes for very rapid adaptation of this universal ASR system. The results we obtain significantly outperform results obtained by many competing approaches on the NIST LoReHLT 2017 Evaluation datasets

Czech name

—

Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

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

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2018

Confidentiality

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

Article name in the collection

Proceedings of Interspeech

ISBN

—

ISSN

1990-9772

e-ISSN

—

Number of pages

5

Pages from-to

2052-2056

Publisher name

International Speech Communication Association

Place of publication

Hyderabad

Event location

Hyderabad, India

Event date

Sep 2, 2018

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000465363900431