The Influence of Lombard Effect on Speech Recognition

The origin of Lombard effect dates back one hundred years. In 1911 Etienne Lombard discovered the psychological effect of speech produced in the presence of noise (Lombard, 1911). The Lombard effect is a phenomenon in which speakers increase their vocal levels in the presence of a loud background noise and make several vocal changes in order t

Advanced Content and Interface Personalization through Conversational Behavior and Affective Embodied Conversational Agents

Conversation is becoming one of the key interaction modes in HMI. As a result, the conversational agents (CAs) have become an important tool in various everyday scenarios. From Apple and Microsoft to Amazon, Google, and Facebook, all have adapted their own variations of CAs. The CAs range from chatbots and 2D, carton-like implementations of talking heads to fully articulated embodied conversational agents performing interaction in various concepts. Recent studies in the field of face-to-face conversation show that the most natural way to implement interaction is through synchronized verbal and co-verbal signals (gestures and expressions). Namely, co-verbal behavior represents a major source of discourse cohesion. It regulates communicative relationships and may support or even replace verbal counterparts. It effectively retains semantics of the information and gives a certain degree of clarity in the discourse. In this chapter, we will represent a model of generation and realization of more natural machine-generated output

Context-dependent factored language models

The incorporation of grammatical information into speech recognition systems is often used to increase performance in morphologically rich languages. However, this introduces demands for sufficiently large training corpora and proper methods of using the additional information. In this paper, we present a method for building factored language models that use data obtained by morphosyntactic tagging. The models use only relevant factors that help to increase performance and ignore data from other factors, thus also reducing the need for large morphosyntactically tagged training corpora. Which data is relevant is determined at run-time, based on the current text segment being estimated, i.e., the context. We show that using a context-dependent model in a two-pass recognition algorithm, the overall speech recognition accuracy in a Broadcast News application improved by 1.73% relatively, while simpler models using the same data achieved only 0.07% improvement. We also present a more detailed error analysis based on lexical features, comparing first-pass and second-pass results

Automated fingerprint identification system application for system\u27s equal error rate evaluation

Automated fingerprint identification system has an increasingly important rolein modern times. This study presents the steps of the automated fingerprint identification system and presents an application for fingerprint identification and system\u27s equal error rate evaluation. The algorithm for fingerprint image enhancement is a key element of the system. A fingerprint image can be damaged, damp, too dry, worn, scratched, etc. Therefore it is necessary to enhance the image to the point where we can obtain a clearly defined structure of ridges and valleys and consequently also correctly determined features. This study also presents a comparison of error rate evaluation between the original fingerprint image and the enhanced fingerprintimage, and introduces an application for fingerprint matching. The matching algorithm compares two fingerprints and establishes a correct match, if the fingerprints belong to the same person, or a non-match, if they belong to different persons

Pragmatične vloge krščanskih izrazov v vsakdanjem govoru

Different kinds of pragmatic expressions in spoken discourse, such as discourse markers, interjections, topic orientation markers, pragmatic deictics, general extenders, etc., have attracted the attention of researchers over recent decades. However, expressions that have their origins within religions have not as yet been studied from the pragmatic perspective, even though in everyday conversation they are used in non-religious contexts and content-free manners more often than within a religious context. The present study is based on the GOS Slovenian reference speech corpus, and covers the more common Christian expressions used in the corpus data, namely: bog "God", bože "God", marija "Mary", madona "Madonna", jezus "Jesus", hudič "Devil", vrag "Devil". The study attempts to highlight the contexts in which these expressions are used, as well as the pragmatic functions they perform.Različni pragmatični izrazi v govorjenem diskurzu, kot so diskurzni označevalci, medmeti, kažipoti, označevalci propozicijske vsebine ipd., so bili v zadnjih desetletjih deležni precejšnje pozornosti raziskovalcev. Toda izrazi, ki imajo svoj izvor v religiji, kot so bog, hudič, marija, madona ipd., s pragmatične perspektive niso bili sistematično raziskani, čeprav jih v vsakdanji govorni komunikaciji pogosteje uporabljamo v nereligioznem pomenu, kot vrsto pragmatičnih izrazov, kakor v njihovem izvornem religioznem pomenu. Raziskava temelji na slovenskem referenčnem govornem korpusu GOS in zajame najpogostejše krščanske izraze, ki jih najdemo v njem. To so: bog, bože, marija, madona, jezus, hudič, vrag. Osvetliti skušamo, v kakšnih kontekstih so ti izrazi rabljeni in kakšne so njihove pragmatične vloge