Design and Evaluation of Shared Prosodic Annotation for Spontaneous French Speech: From Expert Knowledge to Non-Expert Annotation

International audienceIn the area of large French speech corpora, there is a demonstrated need for a common prosodic notation system allowing for easy data exchange, comparison, and automatic annotation. The major questions are: (1) how to develop a single simple scheme of prosodic transcription which could form the basis of guidelines for non-expert manual annotation (NEMA), used for linguistic teaching and research; (2) based on this NEMA, how to establish reference prosodic corpora (RPC) for different discourse genres (Cresti and Moneglia, 2005); (3) how to use the RPC to develop corpus-based learning methods for automatic prosodic labelling in spontaneous speech (Buhman et al., 2002; Tamburini and Caini 2005, Avanzi, et al. 2010). This paper presents two pilot experiments conducted with a consortium of 15 French experts in prosody in order to provide a prosodic transcription framework (transcription methodology and transcription reliability measures) and to establish reference prosodic corpora in French

Integrating Syntactic and Prosodic Information for the Efficient Detection of Empty Categories

We describe a number of experiments that demonstrate the usefulness of prosodic information for a processing module which parses spoken utterances with a feature-based grammar employing empty categories. We show that by requiring certain prosodic properties from those positions in the input where the presence of an empty category has to be hypothesized, a derivation can be accomplished more efficiently. The approach has been implemented in the machine translation project VERBMOBIL and results in a significant reduction of the work-load for the parser.Comment: To appear in the Proceedings of Coling 1996, Copenhagen. 6 page

SEA_AP: una herramienta de segmentación y etiquetado para el análisis prosódico

This paper introduces a tool that performs segmentation and labelling of sound chains in phono units, syllables and/or words departing from a sound signal and its corresponding orthographic transcription. In addition, it also integrates acoustic analysis scripts applied to the Praat programme with the aim of reducing the time spent on tasks related to analysis, correction, smoothing and generation of graphics of the melodic curve. The tool is implemented for Galician, Spanish and Brazilian Portuguese. Our goal is to contribute, by means of this application, to automatize some of the tasks of segmentation, labelling and prosodic analysis, since these tasks require a large investment of time and human resources.En este artículo se presenta una herramienta que realiza la segmentación y el etiquetado de cadenas sonoras en unidades de fono, sílaba y/o palabra partiendo de una señal sonora y de su correspondiente transcripción ortográfica. Además, integra scripts de análisis acústico que se ejecutan sobre el programa Praat con el fin de reducir el tiempo invertido en las tareas de análisis, corrección, suavizado y generación de gráficos de la curva melódica. La herramienta está implementada para gallego, español y portugués de Brasil. Nuestro objetivo es contribuir con esta aplicación a automatizar algunas de las labores de segmentación, etiquetado y análisis prosódico, pues constituyen tareas que requieren una gran inversión de tiempo y de recursos humanos.This work would have not been possible without the help of the Spanish Government (Project ‘SpeechTech4All’ TEC2012-38939-C03-01), the European Regional Development Fund (ERDF), the Government of the Autonomous Community of Galicia (GRC2014/024, “Consolidación de Unidades de Investigación: Proyecto AtlantTIC” CN2012/160) and the “Red de Investigación TecAnDAli” from the Council of Culture, Education and University Planning, Xunta de GaliciaS

Tagging Prosody and Discourse Structure in Elicited Spontaneous Speech

This paper motivates and describes the annotation and analysis of prosody and discourse structure for several large spoken language corpora. The annotation schema are of two types: tags for prosody and intonation, and tags for several aspects of discourse structure. The choice of the particular tagging schema in each domain is based in large part on the insights they provide in corpus-based studies of the relationship between discourse structure and the accenting of referring expressions in American English. We first describe these results and show that the same models account for the accenting of pronouns in an extended passage from one of the Speech Warehouse hotel-booking dialogues. We then turn to corpora described in Venditti [Ven00], which adapts the same models to Tokyo Japanese. Japanese is interesting to compare to English, because accent is lexically specified and so cannot mark discourse focus in the same way. Analyses of these corpora show that local pitch range expansion serves the analogous focusing function in Japanese. The paper concludes with a section describing several outstanding questions in the annotation of Japanese intonation which corpus studies can help to resolve.Work reported in this paper was supported in part by a grant from the Ohio State University Office of Research, to Mary E. Beckman and co-principal investigators on the OSU Speech Warehouse project, and by an Ohio State University Presidential Fellowship to Jennifer J. Venditti

Investigating variation in Arabic intonation : : the case for a multi-level corpus approach

This paper provides a first description of the intonational patterns of San‘aani Arabic (SA, the dialect of Arabic spoken in the capital of Yemen) and a comparison of these patterns with those observed in Cairene Arabic (CA), revealing differences between the two varieties which mirror cross-linguistic prosodic variation. The SA analysis is based on qualitative transcription of portions of a multi-level corpus, including read speech sentences, a narrative retold from memory and a sociolinguistic data collection tool which yields free conversation data in the desired variety as well as information that can be used to confirm which variety is being used. The corpus design and methodology serve as a prototype for larger data collection to document intonational variation in Arabic

Topic in dialogue: prosodic and syntactic features

In this paper we investigate the relationship between phonetic phrasing, tonal pattern and phrase structure in left peripherical sentence topic. Our corpus consists of three task-oriented Italian dialogues. The results of prosodic analysis show that topics are usually associated to the highest pitch values in the Tone Unit, regardless to their actual syntactic position. Syntactic analysis shows that, while topic phrase structure is rather variable, topic function is quite stable, i.e., topics have mostly circumstantial-locative function, and less frequently subject function. Finally, phonetic phrasing, prominence placement and phrase structure shows clearly regular relationships

The Perception of Emotion from Acoustic Cues in Natural Speech

Knowledge of human perception of emotional speech is imperative for the development of emotion in speech recognition systems and emotional speech synthesis. Owing to the fact that there is a growing trend towards research on spontaneous, real-life data, the aim of the present thesis is to examine human perception of emotion in naturalistic speech. Although there are many available emotional speech corpora, most contain simulated expressions. Therefore, there remains a compelling need to obtain naturalistic speech corpora that are appropriate and freely available for research. In that regard, our initial aim was to acquire suitable naturalistic material and examine its emotional content based on listener perceptions. A web-based listening tool was developed to accumulate ratings based on large-scale listening groups. The emotional content present in the speech material was demonstrated by performing perception tests on conveyed levels of Activation and Evaluation. As a result, labels were determined that signified the emotional content, and thus contribute to the construction of a naturalistic emotional speech corpus. In line with the literature, the ratings obtained from the perception tests suggested that Evaluation (or hedonic valence) is not identified as reliably as Activation is. Emotional valence can be conveyed through both semantic and prosodic information, for which the meaning of one may serve to facilitate, modify, or conflict with the meaning of the other—particularly with naturalistic speech. The subsequent experiments aimed to investigate this concept by comparing ratings from perception tests of non-verbal speech with verbal speech. The method used to render non-verbal speech was low-pass filtering, and for this, suitable filtering conditions were determined by carrying out preliminary perception tests. The results suggested that nonverbal naturalistic speech provides sufficiently discernible levels of Activation and Evaluation. It appears that the perception of Activation and Evaluation is affected by low-pass filtering, but that the effect is relatively small. Moreover, the results suggest that there is a similar trend in agreement levels between verbal and non-verbal speech. To date it still remains difficult to determine unique acoustical patterns for hedonic valence of emotion, which may be due to inadequate labels or the incorrect selection of acoustic parameters. This study has implications for the labelling of emotional speech data and the determination of salient acoustic correlates of emotion

Towards Understanding Egyptian Arabic Dialogues

Labelling of user's utterances to understanding his attends which called Dialogue Act (DA) classification, it is considered the key player for dialogue language understanding layer in automatic dialogue systems. In this paper, we proposed a novel approach to user's utterances labeling for Egyptian spontaneous dialogues and Instant Messages using Machine Learning (ML) approach without relying on any special lexicons, cues, or rules. Due to the lack of Egyptian dialect dialogue corpus, the system evaluated by multi-genre corpus includes 4725 utterances for three domains, which are collected and annotated manually from Egyptian call-centers. The system achieves F1 scores of 70. 36% overall domains.Comment: arXiv admin note: substantial text overlap with arXiv:1505.0308

Corpora compilation for prosody-informed speech processing

Research on speech technologies necessitates spoken data, which is usually obtained through read recorded speech, and specifically adapted to the research needs. When the aim is to deal with the prosody involved in speech, the available data must reflect natural and conversational speech, which is usually costly and difficult to get. This paper presents a machine learning-oriented toolkit for collecting, handling, and visualization of speech data, using prosodic heuristic. We present two corpora resulting from these methodologies: PANTED corpus, containing 250 h of English speech from TED Talks, and Heroes corpus containing 8 h of parallel English and Spanish movie speech. We demonstrate their use in two deep learning-based applications: punctuation restoration and machine translation. The presented corpora are freely available to the research community