Audiovisual annotation procedure for multi-view field recordings

Audio and video parts of an audiovisual document interact to produce an audiovisual, or multi-modal, perception. Yet, automatic analysis on these documents are usually based on separate audio and video annotations. Regarding the audiovisual content, these annotations could be incomplete, or not relevant. Besides, the expanding possibilities of creating audiovisual documents lead to consider different kinds of contents, including videos filmed in uncontrolled conditions (i.e. fields recordings), or scenes filmed from different points of view (multi-view). In this paper we propose an original procedure to produce manual annotations in different contexts, including multi-modal and multi-view documents. This procedure, based on using both audio and video annotations, ensures consistency considering audio or video only, and provides additionally audiovisual information at a richer level. Finally, different applications are made possible when considering such annotated data. In particular, we present an example application in a network of recordings in which our annotations allow multi-source retrieval using mono or multi-modal queries

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

Automated speech and audio analysis for semantic access to multimedia

The deployment and integration of audio processing tools can enhance the semantic annotation of multimedia content, and as a consequence, improve the effectiveness of conceptual access tools. This paper overviews the various ways in which automatic speech and audio analysis can contribute to increased granularity of automatically extracted metadata. A number of techniques will be presented, including the alignment of speech and text resources, large vocabulary speech recognition, key word spotting and speaker classification. The applicability of techniques will be discussed from a media crossing perspective. The added value of the techniques and their potential contribution to the content value chain will be illustrated by the description of two (complementary) demonstrators for browsing broadcast news archives

An audiovisual corpus of guided tours in cultural sites : data collection protocols in the CHROME project

Creating interfaces for cultural heritage access is considered a fundamental research field because of the many beneficial effects it has on society. In this era of significant advances towards natural interaction with machines and deeper understanding of social communication nuances, it is important to investigate the communicative strategies human experts adopt when delivering contents to the visitors of cultural sites, as this allows the creation of a strong theoretical background for the development of efficient conversational agents. In this work, we present the data collection and annotation protocols adopted for the ongoing creation of the reference material to be used in the Cultural Heritage Resources Orienting Multimodal Experiences (CHROME) project to accomplish that goa

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Legal knowledge acquisition and multimedia applications

Search, retrieval, and management of multimedia contents are challenging tasks for users and researchers alike. The aim of e-sentencias Project is to develop a software-hardware system for the global management of the multimedia contents produced by the Spanish Civil Courts. We apply technologies such as the Semantic Web, ontologies, NLP techniques, audio-video segmentation and IR. The ultimate goal is to obtain an automatic classification of images and segments of the audiovisual records that, coupled with textual semantics, allows anefficient navigation and retrieval of judicial documents and additional legal sources

Multimedia search without visual analysis: the value of linguistic and contextual information

This paper addresses the focus of this special issue by analyzing the potential contribution of linguistic content and other non-image aspects to the processing of audiovisual data. It summarizes the various ways in which linguistic content analysis contributes to enhancing the semantic annotation of multimedia content, and, as a consequence, to improving the effectiveness of conceptual media access tools. A number of techniques are presented, including the time-alignment of textual resources, audio and speech processing, content reduction and reasoning tools, and the exploitation of surface features

From media crossing to media mining

This paper reviews how the concept of Media Crossing has contributed to the advancement of the application domain of information access and explores directions for a future research agenda. These will include themes that could help to broaden the scope and to incorporate the concept of medium-crossing in a more general approach that not only uses combinations of medium-specific processing, but that also exploits more abstract medium-independent representations, partly based on the foundational work on statistical language models for information retrieval. Three examples of successful applications of media crossing will be presented, with a focus on the aspects that could be considered a first step towards a generalized form of media mining