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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 was one of four tasks proposed in the MGB challenge, with the aim of advancing the state of the art of automatic speech recognition, speaker diarisation and automatic alignment of subtitles for broadcast media. Four topics...
This paper investigates unsupervised vocabulary and language model self-adaptation (VLA) from just one speech file using the web as a knowledge source and without prior knowledge of topic or domain beyond optional file metadata. Single-file self adaptation is regularly used for acoustic adaptation, but to date, is rarely used for VLA. The method investigated here uses a first-pass transcript or file...
In this paper, we report on our research and progress in Vietnamese Broadcast News transcription, with an emphasis on efficient modeling for more accurate recognition. In the acoustic modeling area, this was achieved through a re-alignment process, which considers all pronunciations for each word and outputs the pronunciation that best matches the acoustic data. The effectiveness of acoustic adaptation...
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