Spell-checking in Spanish: the case of diacritic accents

This article presents the problem of diacritic restoration (or diacritization) in the context of spell-checking, with the focus on an orthographically rich language such as Spanish. We argue that despite the large volume of work published on the topic of diacritization, currently available spell-checking tools have still not found a proper solution to the problem in those cases where both forms of a word are listed in the checker’s dictionary. This is the case, for instance, when a word form exists with and without diacritics, such as continuo ‘continuous’ and continuó ‘he/she/it continued’, or when different diacritics make other word distinctions, as in continúo ‘I continue’. We propose a very simple solution based on a word bigram model derived from correctly typed Spanish texts and evaluate the ability of this model to restore diacritics in artificial as well as real errors. The case of diacritics is only meant to be an example of the possible applications for this idea, yet we believe that the same method could be applied to other kinds of orthographic or even grammatical errors. Moreover, given that no explicit linguistic knowledge is required, the proposed model can be used with other languages provided that a large normative corpus is available.Peer ReviewedPostprint (author’s final draft

An Analysis of the Performances of the CasEN Named Entities Recognition System in the Ester2 Evaluation Campaign

8 pagesIn this paper, we present a detailed and critical analysis of the behaviour of the CasEN named entity recognition system during the French Ester2 evaluation campaign. In this project, CasEN has been confronted with the task of detecting and categorizing named entities in manual and automatic transcriptions of radio broadcastings. At first, we give a general presentation of the Ester2 campaign. Then, we describe our system, based on transducers. Next, we depict how systems were evaluated during this campaign and we report the main official results. Afterwards, we investigate in details the influence of some annotation biases which have significantly affected the estimation of the performances of systems. At last, we conduct an in-depth analysis of the effective errors of the CasEN system, providing us with some useful indications about phenomena that gave rise to errors (e.g. metonymy, encapsulation, detection of right boundaries) and are as many challenges for named entity recognition systems

Acoustic correlates of encoded prosody in written conversation

This thesis presents an analysis of certain punctuation devices such as parenthesis, italics and emphatic spellings with respect to their acoustic correlates in read speech. The class of punctuation devices under investigation are referred to as prosodic markers. The thesis therefore presents an analysis of features of the spoken language which are represented symbolically in text. Hence it is a characterization of aspects of the spoken language which have been transcribed or symbolized in the written medium and then translated back into a spoken form by a reader. The thesis focuses in particular on the analysis of parenthesis, the examination of encoded prominence and emphasis, and also addresses the use of paralinguistic markers which signal attitude or emotion.In an effort to avoid the use of self constructed or artificial material containing arbitrary symbolic or prosodic encodings, all material used for empirical analysis was taken from examples of electronic written exchanges on the Internet, such as from electronic mail messages and from articles posted on electronic newsgroups and news bulletins. This medium of language, which is referred to here as written conversation, provides a rich source of material containing encoded prosodic markers. These occur in the form of 'smiley faces' expressing attitudes or feelings, words highlighted by a number of means such as capitalization, italics, underscore characters, or asterisks, and in the form of dashes or parentheses, which provide suggestions on how the information in a text or sentence may be structured with regard to its informational content.Chapter 2 investigates in detail the genre of written conversation with respect to its place in an emerging continuum between written and spoken language, concentrating on transcriptional devices and their function as indicators of prosody. The implications these symbolic representations bear on the task of reading, by humans as well as machines, are then examined.Chapters 3 and 4 turn to the acoustic analysis of parentheticals and emphasis markers respectively. The experimental work in this thesis is based on readings of a corpus of selected materials from written conversation with the acoustic analysis concentrating on the differences between readings of texts with prosodic markers and readings of the same texts from which prosodic markers have been removed. Finally, the effect of prosodic markers is tested in perception experiments involving both human and resynthesized utterances

Orthographic Transcription: Which Enrichment is required for Phonetization?

International audienceThis paper addresses the problem of the enrichment of transcriptions in the perspective of an automatic phonetization. Phonetization is the process of representing sounds with phonetic signs. There are two general ways to construct a phonetization process: rule based systems (with rules based on inference approaches or proposed by expert linguists) and dictionary based solutions which consist in storing a maximum of phonological knowledge in a lexicon. In both cases, phonetization is based on a manual transcription. Such a transcription is established on the basis of conventions that can differ depending on their working out context. This present study focuses on three different enrichments of such a transcription. Evaluations compare phonetizations obtained from automatic systems to a reference phonetized manually. The test corpus is made of three types of speech in French: conversational speech, read speech and political debate. A specific algorithm for the rule-based system is proposed to deal with enrichments. The final system obtained a phonetization of about 95.2% correct (from 3.7% to 5.6% error rates depending on the corpus)

Recognizing Speech in a Novel Accent: The Motor Theory of Speech Perception Reframed

The motor theory of speech perception holds that we perceive the speech of another in terms of a motor representation of that speech. However, when we have learned to recognize a foreign accent, it seems plausible that recognition of a word rarely involves reconstruction of the speech gestures of the speaker rather than the listener. To better assess the motor theory and this observation, we proceed in three stages. Part 1 places the motor theory of speech perception in a larger framework based on our earlier models of the adaptive formation of mirror neurons for grasping, and for viewing extensions of that mirror system as part of a larger system for neuro-linguistic processing, augmented by the present consideration of recognizing speech in a novel accent. Part 2 then offers a novel computational model of how a listener comes to understand the speech of someone speaking the listener's native language with a foreign accent. The core tenet of the model is that the listener uses hypotheses about the word the speaker is currently uttering to update probabilities linking the sound produced by the speaker to phonemes in the native language repertoire of the listener. This, on average, improves the recognition of later words. This model is neutral regarding the nature of the representations it uses (motor vs. auditory). It serve as a reference point for the discussion in Part 3, which proposes a dual-stream neuro-linguistic architecture to revisits claims for and against the motor theory of speech perception and the relevance of mirror neurons, and extracts some implications for the reframing of the motor theory

Automatic Speech Recognition for Low-resource Languages and Accents Using Multilingual and Crosslingual Information

This thesis explores methods to rapidly bootstrap automatic speech recognition systems for languages, which lack resources for speech and language processing. We focus on finding approaches which allow using data from multiple languages to improve the performance for those languages on different levels, such as feature extraction, acoustic modeling and language modeling. Under application aspects, this thesis also includes research work on non-native and Code-Switching speech

Is 42 the Answer to Everything in Subtitling-oriented Speech Translation?

Subtitling is becoming increasingly important for disseminating information, given the enormous amounts of audiovisual content becoming available daily. Although Neural Machine Translation (NMT) can speed up the process of translating audiovisual content, large manual effort is still required for transcribing the source language, and for spotting and segmenting the text into proper subtitles. Creating proper subtitles in terms of timing and segmentation highly depends on information present in the audio (utterance duration, natural pauses). In this work, we explore two methods for applying Speech Translation (ST) to subtitling: a) a direct end-to-end and b) a classical cascade approach. We discuss the benefit of having access to the source language speech for improving the conformity of the generated subtitles to the spatial and temporal subtitling constraints and show that length is not the answer to everything in the case of subtitling-oriented ST.Comment: Accepted at IWSLT 202