Detail publikace

Unsupervised Word Segmentation from Speech with Attention

GODARD, P. BOITO, M. ONDEL YANG, L. BERARD, A. YVON, F. VILLAVICENCIO, A. BESACIER, L.

Originální název

Unsupervised Word Segmentation from Speech with Attention

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

We present a first attempt to perform attentional word segmentation directly from the speech signal, with the final goal to automatically identify lexical units in a low-resource, unwritten language (UL). Our methodology assumes a pairing between recordings in the UL with translations in a well-resourced language. It uses Acoustic Unit Discovery (AUD) to convert speech into a sequence of pseudo-phones that is segmented using neural soft-alignments produced by a neural machine translation model. Evaluation uses an actual Bantu UL, Mboshi; comparisons to monolingual and bilingual baselines illustrate the potential of attentional word segmentation for language documentation.

Klíčová slova

computational language documentation,encoder-decoder models, attentional models, unsupervised word segmentation.

Autoři

GODARD, P.; BOITO, M.; ONDEL YANG, L.; BERARD, A.; YVON, F.; VILLAVICENCIO, A.; BESACIER, L.

Vydáno

2. 9. 2018

Nakladatel

International Speech Communication Association

Místo

Hyderabad

ISSN

1990-9772

Periodikum

Proceedings of Interspeech

Ročník

2018

Číslo

9

Stát

Francouzská republika

Strany od

2678

Strany do

2682

Strany počet

5

URL

https://www.isca-speech.org/archive/Interspeech_2018/pdfs/1308.pdf

BibTex

@inproceedings{BUT163406,
  author="GODARD, P. and BOITO, M. and ONDEL YANG, L. and BERARD, A. and YVON, F. and VILLAVICENCIO, A. and BESACIER, L.",
  title="Unsupervised Word Segmentation from Speech with Attention",
  booktitle="Proceeding of Interspeech 2018",
  year="2018",
  journal="Proceedings of Interspeech",
  volume="2018",
  number="9",
  pages="2678--2682",
  publisher="International Speech Communication Association",
  address="Hyderabad",
  doi="10.21437/Interspeech.2018-1308",
  issn="1990-9772",
  url="https://www.isca-speech.org/archive/Interspeech_2018/pdfs/1308.pdf"
}

Dokumenty

godard_interspeech2018_1308.pdf