The MGB Challenge: Evaluating Multi-genre Broadcast Media Recognition

This paper describes the Multi-Genre Broadcast (MGB) Challenge at ASRU 2015, an evaluation focused on speech recognition, speaker diarization, and "lightly supervised" alignment of BBC TV recordings. The challenge training data covered the whole range of seven weeks BBC TV output across four channels, resulting in about 1,600 hours of broadcast audio. In addition several hundred million words of BBC subtitle text was provided for language modelling. A novel aspect of the evaluation was the exploration of speech recognition and speaker diarization in a longitudinal setting - i.e. recognition of several episodes of the same show, and speaker diarization across these episodes, linking speakers. The longitudinal tasks also offered the opportunity for systems to make use of supplied metadata including show title, genre tag, and date/time of transmission. This paper describes the task data and evaluation process used in the MGB challenge, and summarises the results obtained

Automatic transcription of multi-genre media archives

This paper describes some recent results of our collaborative work on developing a speech recognition system for the automatic transcription or media archives from the British Broadcasting Corporation (BBC). The material includes a wide diversity of shows with their associated metadata. The latter are highly diverse in terms of completeness, reliability and accuracy. First, we investigate how to improve lightly supervised acoustic training, when timestamp information is inaccurate and when speech deviates significantly from the transcription, and how to perform evaluations when no reference transcripts are available. An automatic timestamp correction method as well as a word and segment level combination approaches between the lightly supervised transcripts and the original programme scripts are presented which yield improved metadata. Experimental results show that systems trained using the improved metadata consistently outperform those trained with only the original lightly supervised decoding hypotheses. Secondly, we show that the recognition task may benefit from systems trained on a combination of in-domain and out-of-domain data. Working with tandem HMMs, we describe Multi-level Adaptive Networks, a novel technique for incorporating information from out-of domain posterior features using deep neural network. We show that it provides a substantial reduction in WER over other systems including a PLP-based baseline, in-domain tandem features, and the best out-of-domain tandem features.This research was supported by EPSRC Programme Grant EP/I031022/1 (Natural Speech Technology).This paper was presented at the First Workshop on Speech, Language and Audio in Multimedia, August 22-23, 2013; Marseille. It was published in CEUR Workshop Proceedings at http://ceur-ws.org/Vol-1012/

The effectiveness of hot water pressurized spray in field conditions to slow the spread of invasive alien species

An array of vectors have been identified that pose a risk of spreading invasive alien species (IAS), from personal protective equipment to large equipment such as vehicles and boats. Biosecurity practices that remove and/or kill IAS reduce the risk of accidental spread. The effectiveness of biosecurity protocols suitable for large equipment is little tested and requires development. One widely-used biosecurity method for large equipment is high-pressure hot water spray machines. This study tests the effectiveness of high-pressure hot water spray to induce mortality in two invasive aquatic plants: floating pennywort (Hydrocotyle ranunculoides) and Australian swamp-stonecrop (Crassula helmsii); and two invasive invertebrates: killer shrimp (Dikerogammarus villosus) and zebra mussel (Dreissena polymorpha) in field conditions. IAS were exposed to hot water spray for a range of durations (5–15 seconds) and from a range of distances (10–30 cm). Further treatments of up to 90 seconds were applied to C. helmsii. Complete survival of D. polymorpha, D. villosus and C. helmsii was seen in all control treatments following exposure to cold water spray. Hot water spray caused complete mortality of D. polymorpha and D. villosus at 10 cm for 15 seconds, demonstrating the effectiveness of the hot water treatment in inducing mortality. However, treatments were less effective when applied at longer distances and shorter durations. In contrast, hot water spray was ineffective in causing mortality in C. helmsii, even at 90 seconds of exposure. Fragmentation and complete mortality was seen in H. ranunculoides following exposure to hot and cold water spray, therefore the pressure of the spray was associated with H. ranunculoides mortality. The use of hot water spray is effective against the aquatic invasive animals tested here, however to ensure complete mortality, the importance of both duration and distance of hot water spray application is highlighted. Hot water spray did cause complete mortality in H. ranunculoides but not in C. helmsii, therefore the need for treatment water containment and safe disposal is paramount to prevent spread of potentially viable propagules

Better off dead: assessment of aquatic disinfectants and thermal shock treatments to prevent the spread of invasive freshwater bivalves

Biosecurity protocols designed to prevent further spread of invasive alien species have become a key component of invader management strategies. Yet, the species-specific efficacy of many biosecurity treatments are frequently unclear or unknown. Invasive quagga, Dreissena bugensis, and zebra mussels, D. polymorpha, are a serious threat to freshwater ecosystems worldwide. Here, we examine the effectiveness of immersion (≤ 90 min) within 2% or 4% solutions for two commonly used disinfectants (Virasure® Aquatic and Virkon® Aquatic) to cause mortality of adult Dreissena bivalves. Further, we assessed the effectiveness of thermal treatments: steam spray (≥ 100 °C; ≤ 120 s); hot air (− 500 °C; ≤ 60 s); and dry ice exposure (− 78 °C; ≤ 300 g; 15 min). Complete mortality of D. polymorpha was observed following exposure to both disinfectants for 90 min, at both concentrations. However, high but incomplete mortality (40–90%) was recorded for D. bugensis across disinfectant treatments. For both species, complete mortality was achieved following 30 s of steam. In addition, 10 s of hot air and 15 min exposure to 300 g of dry ice can both completely killed groups of D. polymorpha. Overall, although the disinfectants did not cause complete mortality, it appears that relatively brief exposure to thermal treatments could be used to curtail the further spread of Dreissena species

Robust Speaker-Adaptive HMM-Based Text-to-Speech Synthesis

AbstractWe present an algorithm for solving the radiative transfer problem on massively parallel computers using adaptive mesh refinement and domain decomposition. The solver is based on the method of characteristics which requires an adaptive raytracer that integrates the equation of radiative transfer. The radiation field is split into local and global components which are handled separately to overcome the non-locality problem. The solver is implemented in the framework of the magneto-hydrodynamics code FLASH and is coupled by an operator splitting step. The goal is the study of radiation in the context of star formation simulations with a focus on early disc formation and evolution. This requires a proper treatment of radiation physics that covers both the optically thin as well as the optically thick regimes and the transition region in particular. We successfully show the accuracy and feasibility of our method in a series of standard radiative transfer problems and two 3D collapse simulations resembling the early stages of protostar and disc formation

Extrinsic Summarization Evaluation: A Decision Audit Task

Abstract. In this work we describe a large-scale extrinsic evaluation of automatic speech summarization technologies for meeting speech. The particular task is a decision audit, wherein a user must satisfy a complex information need, navigating several meetings in order to gain an understanding of how and why a given decision was made. We compare the usefulness of extractive and abstractive technologies in satisfying this information need, and assess the impact of automatic speech recognition (ASR) errors on user performance. We employ several evaluation methods for participant performance, including post-questionnaire data, human subjective and objective judgments, and an analysis of participant browsing behaviour.

The MGB challenge: Evaluating multi-genre broadcast media recognition

This paper describes the Multi-Genre Broadcast (MGB) Challenge at ASRU 2015, an evaluation focused on speech recognition, speaker diarization, and «lightly supervised» alignment of BBC TV recordings. The challenge training data covered the whole range of seven weeks BBC TV output across four channels, resulting in about 1,600 hours of broadcast audio. In addition several hundred million words of BBC subtitle text was provided for language modelling. A novel aspect of the evaluation was the exploration of speech recognition and speaker diarization in a longitudinal setting - i.e. recognition of several episodes of the same show, and speaker diarization across these episodes, linking speakers. The longitudinal tasks also offered the opportunity for systems to make use of supplied metadata including show title, genre tag, and date/time of transmission. This paper describes the task data and evaluation process used in the MGB challenge, and summarises the results obtained