This paper describes the Multi-Genre Broadcast (MGB) Challenge at ASRU 2015, an
evaluation focused on speech recognition, speaker diarization, and" lightly supervised" …

Recurrent neural network language models (RNNLMs) have recently become increasingly
popular for many applications including speech recognition. In previous research RNNLMs …

Abstract The Search and Hyperlinking Task was one of the Brave New Tasks at MediaEval
2012. The Task consisted of two sub-tasks which focused on search and linking in retrieval …

It is common that users are interested in finding video segments, which contain further
information about the video contents in a segment of interest. To facilitate users to find and …

Negative transfer in training of acoustic models for automatic speech recognition has been
reported in several contexts such as domain change or speaker characteristics. This paper …

This paper compares schemes for the selection of multi-genre broadcast data and
corresponding transcriptions for speech recognition model training. Selections of the same …

We describe the University of Sheffield system for participation in the 2015 Multi-Genre
Broadcast (MGB) challenge task of transcribing multi-genre broadcast shows. Transcription …

This paper presents a multi-stage speaker diarisation system with longitudinal Linking
developed on BBC multi-genre data for the 2015 Multi-Genre Broadcast (MGB) challenge …

We describe the alignment systems developed both for the preparation of data for the Multi-
Genre Broadcast (MGB) challenge and for our participation in the transcription and …

Abstract The Search and Anchoring in Video Archives (SAVA) task at MediaEval 2015
consists of two sub-tasks:(i) search for multimedia content within a video archive using …