Articles

_________________________________________________________________________________________________________ Robustness of fine acoustic cues and Speech variability: a Mismatch Negativity study We examined electrophysiological correlates of listener’s sensitivity to fine acoustic cues in intra-speaker variability conditions in order to test the relevance of such cues for the speech perception system. For this purpose, a modified oddball paradigm has …...

_________________________________________________________________________________________________________ Selective orientation of attention and perceptual learning In this experiment we explored the effect of the orientation of attention on speech processing in a categorization task. We oriented the subjects’ attention by providing information about the cues that were relevant for classifying the sounds and by giving feedback after …...

Combination of approaches for speaker role recognition In this article, we are particularly interested in recognizing speaker role inside broadcast news shows. Previous studies highlighted a link between speech spontaneity and speaker roles. An automatic spontaneous speech detection system has already been applied to recognize speaker roles, without any change …...

Improvements on driven decoding system combination This paper proposes an improved driven decoding method for speech recognition system combination. The combination method involves the use of auxiliary transcription as external information source included on primary system decoding process. Auxiliary transcriptions are used to modify search space exploration via linguistic score …...

Robustness and portability of spoken language understanding systems among languages and domains : the PORTMEDIA project The ANR PORTMEDIA projet aimed at complementing the MEDIA corpus so as to foster the development of new performing approaches, including statistical approaches, for the automatic spoken language understanding in the framework of human-machine …...

_________________________________________________________________________________________________________ Exploitation of a classification tolerance margin for improving the estimation of class-based acoustic models for speech recognition This paper presents the...

_________________________________________________________________________________________________________ Acoustical and linguistic masking effects of different languages on the comprehension of French words The goal of our research is to explore linguistic interferences which occur during speech- in-speech comprehension. Intensity, nature and language of the background noise were manipulated. Native French participants had to realize a lexical decision …...

_________________________________________________________________________________________________________ When nasal is more than nasal: Oral articulation of French nasal vowels Lingual and labial articulations of oral and nasal vowels of three Metropolitan French (FM) speakers were recorded using an EMA system. Inter-speaker variation in these oral articulations suggest that the role of motor equivalence is important in …...

In this paper, we present our system descrip- tion in task of Cross-lingual Textual Entail- ment. The goal of this task is to detect entailment relations between two sentences written in different languages. To accomplish this goal, we first translate sentences written in foreign languages into English. Then, we use …...

In this paper we present a report of the two di- fferent runs submitted to the task 8 of Semeval 2012 for the evaluation of Cross-lingual Tex- tual Entailment in the framework of Content Synchronization. Both approaches are based on textual similarity, and the entailment judg- ment (bidirectional, forward, backward …...

inThis paper overviews FBK’s participation the Cross-Lingual Textual Entailment for Content Synchronization task organized within SemEval-2012. Our participation is characterized by using cross-lingual matching features extracted from lexical and semantic phrase tables and dependency relations. The features are used for multi-class and binary classification using SVMs. Using a combi- nation …...

This paper presents CELI’s participation in the SemEval Cross-lingual Textual Entailment for Content Synchronization task. 1...

This article presents the experiments car- ried out at Jadavpur University as part of the participation in Cross-lingual Textual Entailment for Content Synchronization (CLTE) of task 8 @ Semantic Evaluation Exercises (SemEval-2012). The work ex- plores cross-lingual textual entailment as a relation between two texts in different lan- guages and …...

This paper presents a novel approach for building adaptive similarity functions based on cardinality us- ing machine learning. Unlike current approaches that build feature sets using similarity scores, we have developed these feature sets with the cardinal- ities of the commonalities and differences between pairs of objects being compared. This …...

We present the Penn system for SemEval- 2012 Task 6, computing the degree of seman- tic equivalence between two sentences. We explore the contributions of different vector models for computing sentence and word sim- ilarity: Collobert and Weston embeddings as well as two novel approaches, namely eigen- words and selectors. …...

The UOW submissions to the Semantic Tex- tual Similarity task at SemEval-2012 use a supervised machine learning algorithm along with features based on lexical, syntactic and semantic similarity metrics to predict the se- mantic equivalence between a pair of sen- tences. The lexical metrics are based on word- overlap. A …...

There are relatively few entailment heuristics that exploit the directional nature of the entail- ment relation. Cross-Lingual Text Entailment (CLTE), besides introducing the extra dimen- sion of cross-linguality, also requires to de- termine the exact direction of the entailment relation, to provide content synchronization (Negri et al., 2012). Our system …...

In this paper we report the results obtained in the Semantic Textual Similarity (STS) task, with a system primarily developed for textual entailment. Our results are quite promising, getting a run ranked 39 in the official results with overall Pearson, and ranking 29 with the Mean metric. 1...

Sentences that are syntactically quite different can often have similar or same meaning. The SemEval 2012 task of Semantic Textual Sim- ilarity aims at finding the semantic similarity between two sentences. The semantic repre- sentation of Universal Networking Language (UNL), represents only the inherent meaning in a sentence without any …...

This paper describes the University of Sheffield’s submission to SemEval-2012 Task 6: Semantic Text Similarity. Two approaches were developed. The first is an unsupervised technique based on the widely used vector space model and information from WordNet. The second method relies on supervised ma- chine learning and represents each sentence …...