Automatic Detection of Hyperarticulated Speech

Eugenio Ribeiro; Fernando Batista; Isabel Trancoso; Ricardo Ribeiro; David de Matos

doi:10.1007/978-3-319-49169-1_18

Automatic Detection of Hyperarticulated Speech

Eugenio Ribeiro, Fernando Batista, Isabel Trancoso, Ricardo Ribeiro, David de Matos

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Abstract

Hyperarticulation is a speech adaptation that consists of adopting a clearer form of speech in an attempt to improve recognition levels. However, it has the opposite effect when talking to ASR systems, as they are not trained with such kind of speech. We present approaches for automatic detection of hyperarticulation, which can be used to improve the performance of spoken dialog systems. We performed experiments on Let’s Go data, using multiple feature sets and two classification approaches. Many relevant features are speaker dependent. Thus, we used the first turn in each dialog as the reference for the speaker, since it is typically not hyperarticulated. Our best results were above 80 % accuracy, which represents an improvement of at least 11.6 % points over previously obtained results on similar data. We also assessed the classifiers’ performance in scenarios where hyperarticulation is rare, achieving around 98 % accuracy using different confidence thresholds.

Original language	English
Title of host publication	Advances in Speech and Language Technologies for Iberian Languages
Subtitle of host publication	Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings
Editors	Alberto Abad, Alfonso Ortega, António Teixeira, Carmen García Mateo, Carlos D. Martínez Hinarejos, Fernando Perdigão, Fernando Batista, Nuno Mamede
Publisher	Springer Nature Switzerland AG
Pages	182-191
ISBN (Electronic)	978-3-319-49169-1
ISBN (Print)	978-3-319-49168-4
DOIs	https://doi.org/10.1007/978-3-319-49169-1_18
Publication status	Published - Nov 2016
Externally published	Yes
Event	International Conference on Advances in Speech and Language Technologies for Iberian Languages - Lisbon, Portugal Duration: 23 Nov 2016 → 25 Nov 2016 https://link.springer.com/conference/iberspeech

Publication series

Series	Lecture Notes in Computer Science book series
Volume	volume 10077

Series	Lecture Notes in Artificial Intelligence (subseries)
Volume	volume 10077

Conference

Conference	International Conference on Advances in Speech and Language Technologies for Iberian Languages
Abbreviated title	IberSPEECH 2016
Country	Portugal
City	Lisbon
Period	23/11/16 → 25/11/16
Internet address	https://link.springer.com/conference/iberspeech

Keywords

Hyperarticulation
Speech
Let’s Go

Access to Document

10.1007/978-3-319-49169-1_18

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Rage: Realising an Applied Gaming Eco-system

Westera, W., Georgiadis, K., Saveski, G., van Lankveld, G., Bahreini, K., van der Vegt, W., Berkhout, J., Nyamsuren, E., Kluijfhout, E. & Nadolski, R.

1/02/15 → 31/07/19

Project: Research

Cite this

Ribeiro, E., Batista, F., Trancoso, I., Ribeiro, R., & de Matos, D. (2016). Automatic Detection of Hyperarticulated Speech. In A. Abad, A. Ortega, A. Teixeira, C. García Mateo, C. D. Martínez Hinarejos, F. Perdigão, F. Batista, & N. Mamede (Eds.), Advances in Speech and Language Technologies for Iberian Languages: Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings (pp. 182-191). Springer Nature Switzerland AG. Lecture Notes in Computer Science book series, Vol.. volume 10077, Lecture Notes in Artificial Intelligence (subseries), Vol.. volume 10077 https://doi.org/10.1007/978-3-319-49169-1_18

Ribeiro, Eugenio ; Batista, Fernando ; Trancoso, Isabel ; Ribeiro, Ricardo ; de Matos, David. / Automatic Detection of Hyperarticulated Speech. Advances in Speech and Language Technologies for Iberian Languages: Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings. editor / Alberto Abad ; Alfonso Ortega ; António Teixeira ; Carmen García Mateo ; Carlos D. Martínez Hinarejos ; Fernando Perdigão ; Fernando Batista ; Nuno Mamede. Springer Nature Switzerland AG, 2016. pp. 182-191 (Lecture Notes in Computer Science book series, Vol. volume 10077). (Lecture Notes in Artificial Intelligence (subseries), Vol. volume 10077).

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title = "Automatic Detection of Hyperarticulated Speech",

abstract = "Hyperarticulation is a speech adaptation that consists of adopting a clearer form of speech in an attempt to improve recognition levels. However, it has the opposite effect when talking to ASR systems, as they are not trained with such kind of speech. We present approaches for automatic detection of hyperarticulation, which can be used to improve the performance of spoken dialog systems. We performed experiments on Let{\textquoteright}s Go data, using multiple feature sets and two classification approaches. Many relevant features are speaker dependent. Thus, we used the first turn in each dialog as the reference for the speaker, since it is typically not hyperarticulated. Our best results were above 80 % accuracy, which represents an improvement of at least 11.6 % points over previously obtained results on similar data. We also assessed the classifiers{\textquoteright} performance in scenarios where hyperarticulation is rare, achieving around 98 % accuracy using different confidence thresholds.",

keywords = "Hyperarticulation, Speech, Let{\textquoteright}s Go",

author = "Eugenio Ribeiro and Fernando Batista and Isabel Trancoso and Ricardo Ribeiro and {de Matos}, David",

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doi = "10.1007/978-3-319-49169-1_18",

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booktitle = "Advances in Speech and Language Technologies for Iberian Languages",

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note = "International Conference on Advances in Speech and Language Technologies for Iberian Languages, IberSPEECH 2016 ; Conference date: 23-11-2016 Through 25-11-2016",

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Ribeiro, E, Batista, F, Trancoso, I, Ribeiro, R & de Matos, D 2016, Automatic Detection of Hyperarticulated Speech. in A Abad, A Ortega, A Teixeira, C García Mateo, C D. Martínez Hinarejos, F Perdigão, F Batista & N Mamede (eds), Advances in Speech and Language Technologies for Iberian Languages: Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings. Springer Nature Switzerland AG, Lecture Notes in Computer Science book series, vol. volume 10077, Lecture Notes in Artificial Intelligence (subseries), vol. volume 10077, pp. 182-191, International Conference on Advances in Speech and Language Technologies for Iberian Languages, Lisbon, Portugal, 23/11/16. https://doi.org/10.1007/978-3-319-49169-1_18

Automatic Detection of Hyperarticulated Speech. / Ribeiro, Eugenio; Batista, Fernando; Trancoso, Isabel; Ribeiro, Ricardo; de Matos, David.

Advances in Speech and Language Technologies for Iberian Languages: Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings. ed. / Alberto Abad; Alfonso Ortega; António Teixeira; Carmen García Mateo; Carlos D. Martínez Hinarejos; Fernando Perdigão; Fernando Batista; Nuno Mamede. Springer Nature Switzerland AG, 2016. p. 182-191 (Lecture Notes in Computer Science book series, Vol. volume 10077). (Lecture Notes in Artificial Intelligence (subseries), Vol. volume 10077).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

TY - GEN

T1 - Automatic Detection of Hyperarticulated Speech

AU - Ribeiro, Eugenio

AU - Batista, Fernando

AU - Trancoso, Isabel

AU - Ribeiro, Ricardo

AU - de Matos, David

PY - 2016/11

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N2 - Hyperarticulation is a speech adaptation that consists of adopting a clearer form of speech in an attempt to improve recognition levels. However, it has the opposite effect when talking to ASR systems, as they are not trained with such kind of speech. We present approaches for automatic detection of hyperarticulation, which can be used to improve the performance of spoken dialog systems. We performed experiments on Let’s Go data, using multiple feature sets and two classification approaches. Many relevant features are speaker dependent. Thus, we used the first turn in each dialog as the reference for the speaker, since it is typically not hyperarticulated. Our best results were above 80 % accuracy, which represents an improvement of at least 11.6 % points over previously obtained results on similar data. We also assessed the classifiers’ performance in scenarios where hyperarticulation is rare, achieving around 98 % accuracy using different confidence thresholds.

AB - Hyperarticulation is a speech adaptation that consists of adopting a clearer form of speech in an attempt to improve recognition levels. However, it has the opposite effect when talking to ASR systems, as they are not trained with such kind of speech. We present approaches for automatic detection of hyperarticulation, which can be used to improve the performance of spoken dialog systems. We performed experiments on Let’s Go data, using multiple feature sets and two classification approaches. Many relevant features are speaker dependent. Thus, we used the first turn in each dialog as the reference for the speaker, since it is typically not hyperarticulated. Our best results were above 80 % accuracy, which represents an improvement of at least 11.6 % points over previously obtained results on similar data. We also assessed the classifiers’ performance in scenarios where hyperarticulation is rare, achieving around 98 % accuracy using different confidence thresholds.

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KW - Speech

KW - Let’s Go

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M3 - Conference article in proceeding

SN - 978-3-319-49168-4

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BT - Advances in Speech and Language Technologies for Iberian Languages

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Ribeiro E, Batista F, Trancoso I, Ribeiro R, de Matos D. Automatic Detection of Hyperarticulated Speech. In Abad A, Ortega A, Teixeira A, García Mateo C, D. Martínez Hinarejos C, Perdigão F, Batista F, Mamede N, editors, Advances in Speech and Language Technologies for Iberian Languages: Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings. Springer Nature Switzerland AG. 2016. p. 182-191. (Lecture Notes in Computer Science book series, Vol. volume 10077). (Lecture Notes in Artificial Intelligence (subseries), Vol. volume 10077). https://doi.org/10.1007/978-3-319-49169-1_18