Towards a Knowledge Graph based Speech Interface

Applications which use human speech as an input require a speech interface with high recognition accuracy. The words or phrases in the recognised text are annotated with a machine-understandable meaning and linked to knowledge graphs for further processing by the target application. These semantic annotations of recognised words can be represented as a subject-predicate-object triples which collectively form a graph often referred to as a knowledge graph. This type of knowledge representation facilitates to use speech interfaces with any spoken input application, since the information is represented in logical, semantic form, retrieving and storing can be followed using any web standard query languages. In this work, we develop a methodology for linking speech input to knowledge graphs and study the impact of recognition errors in the overall process. We show that for a corpus with lower WER, the annotation and linking of entities to the DBpedia knowledge graph is considerable. DBpedia Spotlight, a tool to interlink text documents with the linked open data is used to link the speech recognition output to the DBpedia knowledge graph. Such a knowledge-based speech recognition interface is useful for applications such as question answering or spoken dialog systems.Comment: Under Review in International Workshop on Grounding Language Understanding, Satellite of Interspeech 201

Pitch-based speech perturbation measures using a novel GCI detection algorithm: Application to pathological voice classification

International audienceClassical pitch-based perturbation measures, such as Jitter and Shimmer, are generally based on detection algorithms of pitch marks which assume the existence of a periodic pitch pattern and/or rely on the linear source-filter speech model. While these assumptions can hold for normal speech, they are generally not valid for pathological speech. The latter can indeed present strong aperiodicity, nonlinearity and turbulence/noise. Recently, we introduced on a novel nonlinear algorithm for Glottal Closure Instants (GCI) detection which has the strong advantage of not making such assumptions. In this paper, we use this new algorithm to compute standard pitch-based perturbation measures and compare its performances to the widely used tool PRAAT. We address the task of classification between normal and pathological speech, and carry out the experiments using the popular MEEI database. The results show that our algorithm leads to significantly higher classification accuracy than PRAAT. Moreover, some important statistical features become significantly discriminative, while they are meaningless when using PRAAT (in the sense that they have almost no discrimination power)

Discrimination between pathological voice categories using matching pursuit

International audienceThere are several methods in the literature for pathological voice classification but there are very few methods which can classify pathological subgroups. An attempt is made here to classify pathological subgroups using matching pursuit decomposition method and is compared with PRAAT. Random forest classifier is used and frequency band of the atoms are used as feature. The result shows that we can classify adductor spasmodic dysphonia, keratosis and vocal nodules in a class of voices consisting of adductor spasmodic dysphonia, keratosis, paralysis, vocal nodules and vocal fold polyps with reasonably good classification accuracy. Both matching pursuit (MP) and PRAAT shows comparable classification scores but using MP is more advantageous over PRAAT since it doesn't rely on pitch information and extraction of pitch information in a pathological signal is a complex problem

Fracture behaviour of Ti/TiN multilayer thin film modeling and experimental validation

Although titanium nitride is used as a hard protective coating, it is brittle. The multilayering of Ti/TiN film improves the nitride coating’s damage tolerance and expands its applications. The influence of layer spacing on multilayer fracture toughness (KIC) is not known and quantification is important for designing a multilayer with enhanced damage tolerance. The effect of multilayering on the crack tip driving force is investigated using finite element method (FEM) in this work. Elastic-plastic mismatch in Ti/TiN system is incorporated in simulation. Numerical simulations are performed for varying layer spacing for Ti/TiN systems. Please click Download on the upper right corner to see the full abstract

A 32-society investigation of the influence of perceived economic inequality on social class stereotyping

International audienceThere is a growing body of work suggesting that social class stereotypes are amplified when people perceive higher levels of economic inequality-that is, the wealthy are perceived as more competent and assertive and the poor as more incompetent and unassertive. The present study tested this prediction in 32 societies and also examines the role of wealth-based categorization in explaining this relationship. We found that people who perceived higher economic inequality were indeed more likely to consider wealth as a meaningful basis for categorization. Unexpectedly, however, higher levels of perceived inequality were associated with perceiving the wealthy as less competent and assertive and the poor as more competent and assertive. Unpacking this further, exploratory analyses showed that the observed tendency to stereotype the wealthy negatively only emerged in societies with lower social mobility and democracy and higher corruption. This points to the importance of understanding how socio-structural features that co-occur with economic inequality may shape perceptions of the wealthy and the poor

Question Answering on Linked Data: Challenges and Future Directions

Question Answering (QA) systems are becoming the inspiring model for the future of search engines. While, recently, datasets underlying QA systems have been promoted from unstructured datasets to structured datasets with semantically highly enriched metadata, question answering systems are still facing serious challenges and are therefore not meeting users' expectations. This paper provides an exhaustive insight of challenges known so far for building QA systems, with a special focus on employing structured data (i.e. knowledge graphs).It thus helps researchers to easily spot gaps to fill with their future research agendas

Active case finding among marginalised and vulnerable populations reduces catastrophic costs due to tuberculosis diagnosis

Background: There is limited evidence on whether active case finding (ACF) among marginalised and vulnerable populations mitigates the financial burden during tuberculosis (TB) diagnosis. Objectives: To determine the effect of ACF among marginalised and vulnerable populations on prevalence and inequity of catastrophic costs due to TB diagnosis among TB-affected households when compared with passive case finding (PCF). Methods: In 18 randomly sampled ACF districts in India, during March 2016 to February 2017, we enrolled all new sputum-smear-positive TB patients detected through ACF and an equal number of randomly selected patients detected through PCF. Direct (medical and non-medical) and indirect costs due to TB diagnosis were collected through patient interviews at their residence. We defined costs due to TB diagnosis as ‘catastrophic’ if the total costs (direct and indirect) due to TB diagnosis exceeded 20% of annual pre-TB household income. We used concentration curves and indices to assess the extent of inequity. Results: When compared with patients detected through PCF (n = 231), ACF patients (n = 234) incurred lower median total costs (US$ 4.6 and 20.4, p < 0.001). The prevalence of catastrophic costs in ACF and PCF was 10.3 and 11.5% respectively. Adjusted analysis showed that patients detected through ACF had a 32% lower prevalence of catastrophic costs relative to PCF [adjusted prevalence ratio (95% CI): 0.68 (0.69, 0.97)]. The concentration indices (95% CI) for total costs in both ACF [−0.15 (−0.32, 0.11)] and PCF [−0.06 (−0.20, 0.08)] were not significantly different from the line of equality and each other. The concentration indices (95% CI) for catastrophic costs in both ACF [−0.60 (−0.81, –0.39)] and PCF [−0.58 (−0.78, –0.38)] were not significantly different from each other: however, both the curves had a significant distribution among the poorest quintiles. Conclusion: ACF among marginalised and vulnerable populations reduced total costs and prevalence of catastrophic costs due to TB diagnosis, but could not address inequity

Patient characteristics, health seeking and delays among new sputum smear positive TB patients identified through active case finding when compared to passive case finding in India.

BackgroundAxshya SAMVAD is an active tuberculosis (TB) case finding (ACF) strategy under project Axshya (Axshya meaning 'free of TB' and SAMVAD meaning 'conversation') among marginalized and vulnerable populations in 285 districts of India.ObjectivesTo compare patient characteristics, health seeking, delays in diagnosis and treatment initiation among new sputum smear positive TB patients detected through ACF and passive case finding (PCF) under the national TB programme in marginalized and vulnerable populations between March 2016 and February 2017.MethodsThis observational analytic study was conducted in 18 randomly sampled Axshya districts. We enrolled all TB patients detected through ACF and an equal number of randomly selected patients detected through PCF in the same settings. Data on patient characteristics, health seeking and delays were collected through record review and patient interviews (at their residence). Delays included patient level delay (from eligibility for sputum examination to first contact with any health care provider (HCP)), health system level diagnosis delay (from contact with first HCP to TB diagnosis) and treatment initiation delays (from diagnosis to treatment initiation). Total delay was the sum of patient level, health system level diagnosis delay and treatment initiation delays.ResultsWe included 234 ACF-diagnosed and 231 PCF-diagnosed patients. When compared to PCF, ACF patients were relatively older (≥65 years, 14% versus 8%, p = 0.041), had no formal education (57% versus 36%, pConclusionAxshya SAMVAD linked the most impoverished communities to TB care and resulted in reduction of health system level diagnosis delay