Constrained speaker linking

In this paper we study speaker linking (a.k.a.\ partitioning) given constraints of the distribution of speaker identities over speech recordings. Specifically, we show that the intractable partitioning problem becomes tractable when the constraints pre-partition the data in smaller cliques with non-overlapping speakers. The surprisingly common case where speakers in telephone conversations are known, but the assignment of channels to identities is unspecified, is treated in a Bayesian way. We show that for the Dutch CGN database, where this channel assignment task is at hand, a lightweight speaker recognition system can quite effectively solve the channel assignment problem, with 93% of the cliques solved. We further show that the posterior distribution over channel assignment configurations is well calibrated.Comment: Submitted to Interspeech 2014, some typos fixe

Creating a Dutch testbed to evaluate the retrieval from textual databases

This paper describes the first large-scale evaluation of information retrieval systems using Dutch documents and queries. We describe in detail the characteristics of the Dutch test data, which is part of the official CLEF multilingual texttual database, and give an overview of the experimental results of companies and research institutions that participated in the first official Dutch CLEF experiments. Judging from these experiments, the handling of language-specific issues of Dutch, like for instance simple morphology and compound nouns, significantly improves the performance of information retrieval systems in many cases. Careful examination of the test collection shows that it serves as a reliable tool for the evaluation of information retrieval systems in the future

Speech-based recognition of self-reported and observed emotion in a dimensional space

The differences between self-reported and observed emotion have only marginally been investigated in the context of speech-based automatic emotion recognition. We address this issue by comparing self-reported emotion ratings to observed emotion ratings and look at how differences between these two types of ratings affect the development and performance of automatic emotion recognizers developed with these ratings. A dimensional approach to emotion modeling is adopted: the ratings are based on continuous arousal and valence scales. We describe the TNO-Gaming Corpus that contains spontaneous vocal and facial expressions elicited via a multiplayer videogame and that includes emotion annotations obtained via self-report and observation by outside observers. Comparisons show that there are discrepancies between self-reported and observed emotion ratings which are also reflected in the performance of the emotion recognizers developed. Using Support Vector Regression in combination with acoustic and textual features, recognizers of arousal and valence are developed that can predict points in a 2-dimensional arousal-valence space. The results of these recognizers show that the self-reported emotion is much harder to recognize than the observed emotion, and that averaging ratings from multiple observers improves performance

Arousal and Valence Prediction in Spontaneous Emotional Speech: Felt versus Perceived Emotion

In this paper, we describe emotion recognition experiments carried out for spontaneous affective speech with the aim to compare the added value of annotation of felt emotion versus annotation of perceived emotion. Using speech material available in the TNO-GAMING corpus (a corpus containing audiovisual recordings of people playing videogames), speech-based affect recognizers were developed that can predict Arousal and Valence scalar values. Two types of recognizers were developed in parallel: one trained with felt emotion annotations (generated by the gamers themselves) and one trained with perceived/observed emotion annotations (generated by a group of observers). The experiments showed that, in speech, with the methods and features currently used, observed emotions are easier to predict than felt emotions. The results suggest that recognition performance strongly depends on how and by whom the emotion annotations are carried out. \u

Impact of basic angle variations on the parallax zero point for a scanning astrometric satellite

Determination of absolute parallaxes by means of a scanning astrometric satellite such as Hipparcos or Gaia relies on the short-term stability of the so-called basic angle between the two viewing directions. Uncalibrated variations of the basic angle may produce systematic errors in the computed parallaxes. We examine the coupling between a global parallax shift and specific variations of the basic angle, namely those related to the satellite attitude with respect to the Sun. The changes in observables produced by small perturbations of the basic angle, attitude, and parallaxes are calculated analytically. We then look for a combination of perturbations that has no net effect on the observables. In the approximation of infinitely small fields of view, it is shown that certain perturbations of the basic angle are observationally indistinguishable from a global shift of the parallaxes. If such perturbations exist, they cannot be calibrated from the astrometric observations but will produce a global parallax bias. Numerical simulations of the astrometric solution, using both direct and iterative methods, confirm this theoretical result. For a given amplitude of the basic angle perturbation, the parallax bias is smaller for a larger basic angle and a larger solar aspect angle. In both these respects Gaia has a more favourable geometry than Hipparcos. In the case of Gaia, internal metrology is used to monitor basic angle variations. Additionally, Gaia has the advantage of detecting numerous quasars, which can be used to verify the parallax zero point.Comment: 8 pages, 2 figures; Accepted for publication in Astronomy & Astrophysic

Dealing with Phrase Level Co-Articulation (PLC) in speech recognition: A first approach

Whereas nowadays within-word co-articulation effects are usually sufficiently dealt with in automatic speech recognition, this is not always the case with phrase level co-articulation effects (PLC). This paper describes a first approach in dealing with phrase level co-articulation by applying these rules on the reference transcripts used for training our recogniser and by adding a set of temporary PLC phones that later on will be mapped on the original phones. In fact we temporarily break down acoustic context into a general and a PLC context. With this method, more robust models could be trained because phones that are confused due to PLC effects like for example /v/-/f/ and /z/-/s/, receive their own models. A first attempt to apply this method is described

Ultrasonication in Soy Processing for Enhanced Protein and Sugar Yields and Subsequent Bacterial Nisin Production

Soy protein recovery from hexane-defatted soybean flakes using conventional methods is generally low. Importantly, some tightly-bound sugar in the soy flakes ends up in soy protein, thereby deteriorating the usefulness and quality of soy protein as a food ingredient. This research investigated the use of high-power ultrasound prior to soy protein extraction to simultaneously enhance protein yield and facilitate more sugar release in soy whey. The nutrient-rich soy whey was then used as a cheap growth medium to produce high-value nisin using Lactococcus lactis subsp. lactis. A nisin sensitive organism Micrococcus luteus was used as an indicator organism for international unit determination of nisin production as compared to standard. Soy flakes and water was mixed at the ratio of 1:10 (w/w). The slurry was then sonicated for 15, 30, 60 and 120 sec at a frequency of 20 kHz. The ultrasonic amplitude was maintained at 84 µmpp (peak to peak amplitude in µm) for all sonication durations. The results showed that with ultrasound pretreatment, the protein yield improved as much as by 46% in soy extract and sugar release by 50% with respect to nonsonicated samples (control). To maximize nisin production from soy whey, different parameters, such as aeration/agitation and incubation period were optimized. Nisin production from standard medium, DeMan, Rogosa and Sharpe (MRS) and soy whey was tested and compared. Maximum nisin production was achieved in stationary conditions and showed a continuous increase in yield till 48h of incubation (incubation period beyond that was not tested). Maximum nisin yield of 1.78 g/L of soy whey was obtained at 30°C and pH of 4.5 as opposed to 2.96 g/L of nisin with MRS medium

Why are the K dwarfs in the Pleiades so Blue?

The K dwarfs in the Pleiades fall nearly one half magnitude below a main sequence isochrone when plotted in a color-magnitude diagram utilizing V magnitude as the luminosity index and B-V as the color index. This peculiarity has been known for forty years but has gone unexplained and mostly ignored. When compared to Praesepe members, the Pleiades K dwarfs again are subluminous (or blue) in a color-magnitude diagram using B-V as the color index. However, using V-I as the color index, stars in the two clusters are coincident to M_V ~ 10; using V-K as the color index, Pleiades late K and M stars fall above the main sequence locus defined by Praesepe members. We believe that the anomalous spectral energy distributions for the Pleiades K dwarfs, as compared to older clusters, are a consequence of rapid stellar rotation and may be primarily due to spottedness. If so, the required areal filling factor for the cool component has to be very large (=> 50%). Weak-lined T Tauri stars have similar color anomalies, and we suspect this is a common feature of all very young K dwarfs (sp. type > K3). The peculiar spectral energy distribution needs to be considered in deriving accurate pre-main sequence isochrone-fitting ages for clusters like the Pleiades since the age derived will depend on the temperature index used.Comment: 41 pages, 15 figures, AASTeX5.0. Accepted 05 May 2003; Scheduled for publication in the Astronomical Journal (August 2003