## 1 Introduction  
Albayzin is a series of technological evaluations open to the scientific community in order to propose challenges and datasets to work with in different fields of the broad area of speech technologies. Organized since 2006 and supported by the Spanish Thematic Network on Speech Technologies (RTTH) (Red Tematica en Tecnologias del Habla (RTTH) [[http://www.rthabla.es](http://www.rthabla.es)]([http://www.rthabla.es](http://www.rthabla.es))), in 2018, the broadcast media area was addressed. Jointly with Radio Television Espanola, RTVE (Radiotelevision Espanola (RTVE): [[http://www.rtve.es](http://www.rtve.es)]([http://www.rtve.es](http://www.rtve.es))), the Spanish Public Broadcast Corporation, Vivolab (Vivolab [[http://vivolab.unizar.es](http://vivolab.unizar.es)]([http://vivolab.unizar.es](http://vivolab.unizar.es))), the speech research group at the University of Zaragoza, proposed a set of technological evaluations in the areas of speaker diarization and speech and face recognition. These evaluations were also supported by the RTVE Chair at the University of Zaragoza (Catedra RTVE de la Universidad de Zaragoza: [[http://catedrartve.unizar.es](http://catedrartve.unizar.es)]([http://catedrartve.unizar.es](http://catedrartve.unizar.es))). The dataset provided to participants included more than 500 h of broadcast content, spanning a broad range of genres. In addition, part of the media content was provided with subtitles, human revised transcriptions, and speaker labels.  
Since 1996, when DARPA [1] presented the HUB-4 broadcast news corpora, several evaluations for broadcast speech related tasks have been organized, most of them in English [2]. Campaigns have been also carried out in other languages such as the ESTER evaluations in French [3, 4], the Technologyand Corpora for Speech to Speech Translation (TC-STAR) evaluation in Mandarin [5], the National Institute of Standards and Technology (NIST) Rich Transcription evaluations in 2003 and 2004 with data in English, Mandarin, and Arabic, the Albayzin 2010 evaluation campaign in Catalan [6; 7], the Albayzin 2012, 2014, and 2016 in Spanish [8; 9; 10; 11], and more recently, the Multi-Genre Broadcast (MGB) Challenge with data in English and Arabic 2 [12; 13; 14]. In other areas apart from broadcast speech, several evaluation campaigns have been proposed such as the ones organized in the scope of the Zero Resource Speech Challenge [15; 16], the TC-STAR evaluation on recordings of the European Parliament's sessions in English and Spanish [5], or the MediaEval evaluation of multimodal search and hyperlinking [17].  
As a way to measure the performance of different techniques and approaches, in this 2018 edition, the IberSpeech-RTVE Challenge Evaluation campaign was proposed in three different conditions: speech-to-text transcription (STT), speaker diarization (SD), and multimodal diarization (MD). Twenty-two teams registered to the challenge, and eighteen submitted systems in at least one of the three proposed tasks. In this paper, we describe the challenge and the data provided by the organization to the participants. We also provide a description of the systems presented to the evaluation, their results, and a set of conclusions that can be drawn from this evaluation campaign.  
This paper is organized as follows. In Section 2, the RTVE2018 database is presented. Section 3 describes the three evaluation tasks, speech-to-text transcription, speaker diarization, and multimodal diarization. Section 4 provides a brief description of the main features of the submitted systems. Section 5 presents results, and Section 6 gives conclusions.