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"en": "## Introduction\r\nThe research material consists of the Finnish first encounters dialogue corpus collected as part of the NOMCO project, a Nordic cooperation project. The project aim for developing and analyzing multi-modal spoken language corpora in the Nordic countries, and to compare communication strategies in three closely related languages (Danish, Finnish, and Swedish). The main goals of the project are the following:\r\n\r\n1. Providing comparative annotated multimodal data.\r\n2. Using these data to investigate specific communicative phenomena such as feedback and turn-taking.\r\n3. Developing, extending and adapting models of multimodal interactive communication management that can serve as a basis for interactive systems;\r\n4. Applying machine learning techniques in order to test the possibilities for automatically recognizing or predicting hand gestures, head movements and facial expressions with different interactive communication functions. \r\n\r\nWithin the project, dialog corpora using the same activity type, first encounters, have been collected in the different languages: using the same activity type, comparisons between languages and cultures can be enabled.\r\n\r\n## Data collection\r\nThe interactions in the first encounters corpora involve two subjects who are standing in front of a light background. The participants were instructed to get to know each other in a short interaction, as they might do at a party or a reception. After the recording they answered a questionnaire about their reactions to both the interlocutor and the interaction setting. The dataset consist of 16 video recordings of first-encounter interactions in Finnish. Video recordings show both participants at the same time as well as each participant individually, and there is also a mosaic version with the individual and the joint video streamed together in one video. In this study we concentrate on individual behaviours and not on interpersonal communication, and thus used the individual videos rather than videos with both participants as research material.\r\nThe 14 participants did not know each other in advance, and were given the task of getting to know each other by having a conversation. Eleven of the participants had two conversations with a different partner, while three took part in only one conversation. Although one’s conversational activity depends on the partner, it seems useful to distinguish between the first and the second conversation, since in the second one, the speaker is familiar with the recording situation and can therefore feel more relaxed and attentive to the partner. In fact, in terms of the speaking time, the participants seem to speak about 7% more in their first conversation than in the second one, which can be interpreted as supporting this assumption: in the second conversation, they feel more experienced and in control of the situation, so as to follow and let the partner to speak.\r\n\r\n## Dataset statistics and organization\r\nThere are 14 participants, 4 males and 10 females, all native speakers of Finnish. Of the 16 collected conversations, there are 2 male-male conversations, 6 male-female conversations, and 8 female-female conversations. The shortest conversation is 3 minutes 49 seconds and the longest 8 minutes 2 seconds. The average length of the conversations is 6 minutes 25 seconds.\r\n\r\n## Content and annotations\r\nThe dataset provides recording in two primitive types of data: audio and video, which are annotated for three different tasks:\r\n\r\n* The transcriptions are provided in both Finnish, and translated English.\r\n* The laughter annotations mark the laughing events from each speaker.\r\n* The topic annotations, in English, specify discussing topic along the conversation.\r\n\r\nFor more information concerned the structure of the dataset, you can check the Readme.txt included in the dataset."
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"en": "## Introduction\r\nThe DigiSami project (www.helsinki.fi/digisami/) aims to study the effect of digitalisation on small Finno-Ugric language communities and to support visibility and revitalisations of the endangered languages by creating digital content as well as developing language and speech technology tools, resources, and applications that can be used for automatic speech and language processing. The project focuses especially on the North Sami language, and explores various spoken language issues (speaker identification, multimodal conversation analysis, laughing), with the challenging goal of demonstrating viability of an interactive dialogue system in the North Sami language, SamiTalk, following the multilingual open-domain robot application WikiTalk. WikiTalk is an interactive robot application that enables users to find out more about subjects that interest them by discussing with the humanoid robot. They can navigate through the Wikipedia articles, ask for more information on interesting subjects, and get the robot to read the related Wikipedia article for them.\r\n\r\n## Data collection\r\nThe project organsied Sami language data collection and Wikipedia article writing through series of community events. The participants were invited to take part in three different tasks: discussion and writing Wikipedia articles, reading aloud of existing Wikipedia texts, and taking part in a free conversation which was video recorded. The events took place in the central Sami speaking areas, selected so that they represented different North Sami dialects. The locations were three villages in Finland: Utsjoki (Ohcejohka), Inari (Anár) and Ivalo (Avvil), and two villages in Norway: Kautokeino (Guovdageaid) and Karasjoki (Kárásjohka). (see more of the DigiSami data and data collection in).\r\nText readings and conversations were recorded by EDIROL R4Pro four-channel recording device with AKG 417 L-microphones. Two Panasonic HC-X920 video cameras and three GoPro HERO3 cameras were used for video-recordings. Conversational speech was also recorded by the cameras own microphone.\r\nThe reading took place in a calm and normal speaking manner, and the participant could study the articles in advance. The conversations were between two or three people, and the participants were instructed to discuss freely about their own interests or about the Wikipedia articles they were to write (e.g. Sami language, Sami costume, music, reindeer herding, and snow- mobiles). The topics vary from everyday life (next vacation, driving school, cars) to translation between Sami and other languages and to technological tools that have been made to help writing North Sami more correctly. The conversations differ in style: familiar participants have casual conversations and they often refer to things they had been talking about earlier. Conversations between a pupil and a teacher are more formal and resemble interviews rather than conversations.\r\n\r\n## Dataset statistics and organization\r\nThere were 28 participants, 10 men and 18 women. Their age range from 16 to 65 years: 17 were 16-21 years old, five 30-44 years old, and six 49-65 years old. The participants were native speakers of North Sami, and almost all (26) reported using North Sami daily; one participant reported using North Sami weekly and one participant monthly. All participants were bilingual, and spoke either Finnish (Utsjoki, Ivalo, Inari), or Norwegian (Kautokeino and Karasjoki). Most participants had lived their life in the Spmi area, although not in the same place. Ten participants had also lived in bigger cities in the southern part of the area, Oulu and Rovaniemi in Finland and Bergen in Norway, for a short period of time.\r\n\r\n## Contents and annotations\r\nThe dataset provides recording in two primitive types of data: audio and video, which are annotated for three different tasks:\r\n\r\n* The transcriptions are provided in both North Sami, and translated English.\r\n* The laughter annotations mark the laughing events from each speaker.\r\n* The topic annotations, in English, specify discussing topic along the conversation.\r\n\r\nFor more information concerned the structure of the dataset, you can check the Readme.txt included in the dataset."
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