Discourse Particles in French: Prosodic Parameters Extraction and Analysis

Dargnat, Mathilde; Bartkova, Katarina; Jouvet, Denis

doi:10.1007/978-3-319-25789-1_5

Cited by 5 publications

(6 citation statements)

References 16 publications

(9 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In this study, we present a prosodic analysis of three French discourse markers (alors ['so', 'then', 'well'], bon ['well', 'right'], and donc ['so', 'then']) and three English markers (now, so, and well) according to their different pragmatic functions. As we observed in our previous studies on French discourse markers [18], [19], [20], [21], prosodic production of discourse markers depends on their pragmatic function in the context. The present study is focussed on a comparison between prosodic correlates of discourse markers with respect to pragmatic functions, firstly in different speech styles and secondly across different languages.…”

Section: Introductionsupporting

confidence: 52%

Correlation Between Prosody and Pragmatics: Case Study of Discourse Markers in French and English

Lee¹,

Jouvet²,

Bartkova³

et al. 2020

Interspeech 2020

Self Cite

View full text Add to dashboard Cite

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

show abstract

Section: Introductionsupporting

confidence: 52%

Correlation Between Prosody and Pragmatics: Case Study of Discourse Markers in French and English

Lee¹,

Jouvet²,

Bartkova³

et al. 2020

Interspeech 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…In [34], prosodic correlates of a few words that can be used as discourse particles have been analyzed, but using data mainly from prepared speech. Here, as mentioned in Section 2, we consider a much larger set of speech corpora spanning various speaking styles (from storytelling to highly spontaneous speech).…”

Section: Analysis Of a Few Prosodic Correlatesmentioning

confidence: 99%

Analysis and Automatic Classification of Some Discourse Particles on a Large Set of French Spoken Corpora

Jouvet

Bartkova

Dargnat

et al. 2017

Statistical Language and Speech Processing

Self Cite

View full text Add to dashboard Cite

In French, quite a number of words and expressions are frequently used as discourse particles in spoken language, especially in spontaneous speech. The semantic load of these words or expressions differ whether they are used as discourse particles or not. Therefore, the correct identification of their discourse function remains of great importance. In this paper the distribution of the discourse function (or not discourse function), and of the detailed discourse functions of some of these words, is studied on a large set of French corpora ranging from prepared speech (e.g. storytelling and broadcast news) to spontaneous speech (e.g. interviews and interactions between people). The paper is focused on a subset of discourse particles that are recurrent in the considered corpora. The discourse function of a few thousand occurrences of these words have been manually annotated. A statistical analysis of the functions of the words is presented and discussed with respect to the types of spoken corpora. Finally, some statistics with respect to a few prosodic correlates of the discourse particles are presented, as well as some results of automatic classification and detection of the word function (discourse particle or not) using prosodic features.

show abstract

“…This include also the position of the word in its prosodic group, determined automatically as described above in Section 4.2. Experiments have also been carried out on automatic classification of the occurrences as discourse particle or not using their prosodic characteristics [14], [22].…”

Section: Prosodic Correlates Of Discourse Particlesmentioning

confidence: 99%

Speech Processing and Prosody

Jouvet

2019

Text, Speech, and Dialogue

Self Cite

View full text Add to dashboard Cite

The prosody of the speech signal conveys information over the linguistic content of the message: prosody structures the utterance, and also brings information on speaker's attitude and speaker's emotion. Duration of sounds, energy and fundamental frequency are the prosodic features. However their automatic computation and usage are not obvious. Sound duration features are usually extracted from speech recognition results or from a force speech-text alignment. Although the resulting segmentation is usually acceptable on clean native speech data, performance degrades on noisy or not non-native speech. Many algorithms have been developed for computing the fundamental frequency, they lead to rather good performance on clean speech, but again, performance degrades in noisy conditions. However, in some applications, as for example in computer assisted language learning, the relevance of the prosodic features is critical; indeed, the quality of the diagnostic on the learner's pronunciation will heavily depend on the precision and reliability of the estimated prosodic parameters. The paper considers the computation of prosodic features, shows the limitations of automatic approaches, and discusses the problem of computing confidence measures on such features. Then the paper discusses the role of prosodic features and how they can be handled for automatic processing in some tasks such as the detection of discourse particles, the characterization of emotions, the classification of sentence modalities, as well as in computer assisted language learning and in expressive speech synthesis.

show abstract

Discourse Particles in French: Prosodic Parameters Extraction and Analysis

Cited by 5 publications

References 16 publications

Correlation Between Prosody and Pragmatics: Case Study of Discourse Markers in French and English

Correlation Between Prosody and Pragmatics: Case Study of Discourse Markers in French and English

Analysis and Automatic Classification of Some Discourse Particles on a Large Set of French Spoken Corpora

Speech Processing and Prosody

Contact Info

Product

Resources

About