Language modeling and transcription of the TED corpus lectures

Transcribing lectures is a challenging task, both in acoustic and in language modeling. In this work, we present our first results on the automatic transcription of lectures from the TED corpus, recently released by ELRA and LDC. In particular, we concentrated our effort on language modeling. Baseline acoustic and language models were developed using respectively 8 hours of TED transcripts and various types of texts: conference proceedings, lecture transcripts, and conversational speech transcripts. Then, adaptation of the language model to single speakers was investigated by exploiting different kinds of information: automatic transcripts of the talk, the title of the talk, the abstract and, finally, the paper. In the last case, a 39.2% WER was achieved

pour une prise en compte du genre dans les actions d'insertion en milieu rural

les actions d'insertion sociale et professionnelle en direction des femmes en milieu rural ont permis de donner une visibilité aux problèmes des femmes. mais elles se heurtent à un marché de l'emploi peu diversifié et à des trajectoires individuelles extrêmement hétérogène

An Arabic-Hebrew parallel corpus of TED talks

We describe an Arabic-Hebrew parallel corpus of TED talks built upon WIT3, the Web inventory that repurposes the original content of the TED website in a way which is more convenient for MT researchers. The benchmark consists of about 2,000 talks, whose subtitles in Arabic and Hebrew have been accurately aligned and rearranged in sentences, for a total of about 3.5M tokens per language. Talks have been partitioned in train, development and test sets similarly in all respects to the MT tasks of the IWSLT 2016 evaluation campaign. In addition to describing the benchmark, we list the problems encountered in preparing it and the novel methods designed to solve them. Baseline MT results and some measures on sentence length are provided as an extrinsic evaluation of the quality of the benchmark

Breath‐by‐breath oxygen uptake during running: Effects of different calculation algorithms

New Findings What is the central question of this study? Breath‐by‐breath gas exchange analysis during treadmill exercise can be disturbed by different breathing patterns depending on cadence, and the flow sensor might be subjected to variable mechanical stress. It is still unclear whether the outcomes of the gas exchange algorithms can be affected by running at different speeds. What is the main finding and its importance? Practically, the three investigated breath‐by‐breath algorithms ('Wessel', 'expiration‐only' and 'independent breath') provided similar average gas exchange values for steady‐state conditions. The 'independent breath' algorithm showed the lowest breath‐by‐breath fluctuations in the gas exchange data compared with the other investigated algorithms, both at steady state and during incremental exercise. AbstractRecently, a new breath‐by‐breath gas exchange calculation algorithm (called 'independent breath') was proposed. In the present work, we aimed to compare the breath‐by‐breath O2 uptake () values assessed in healthy subjects undergoing a running protocol, as calculated applying the 'independent breath' algorithm or two other commonly used algorithms. The traces of respiratory flow, O2 and CO2 fractions, used by the calculation algorithms, were acquired at the mouth on 17 volunteers at rest, during running on a treadmill at 6.5 and 9.5 km h−1, and thereafter up to volitional fatigue. Within‐subject averages and standard deviations of breath‐by‐breath were calculated for steady‐state conditions; the data of the incremental phase were analysed by means of linear regression, and their root mean square was assumed to be an index of the breath‐by‐breath fluctuations. The average values obtained with the different algorithms were significantly different (P < 0.001); nevertheless, from a practical point of view the difference could be considered 'small' in all the investigated conditions (effect size <0.3). The standard deviations were significantly lower for the 'independent breath' algorithm (post hoc contrasts, P < 0.001), and the slopes of the relationships with the corresponding data yielded by the other algorithms were <0.70. The root mean squares of the linear regressions calculated for the incremental phase were also significantly lower for the 'independent breath' algorithm, and the slopes of the regression lines with the corresponding values obtained with the other algorithms were <0.84. In conclusion, the 'independent breath' algorithm yielded the least breath‐by‐breath O2 uptake fluctuation, both during steady‐state exercise and during incremental running

CTC-based Compression for Direct Speech Translation

Previous studies demonstrated that a dynamic phone-informed compression of the input audio is beneficial for speech translation (ST). However, they required a dedicated model for phone recognition and did not test this solution for direct ST, in which a single model translates the input audio into the target language without intermediate representations. In this work, we propose the first method able to perform a dynamic compression of the input indirect ST models. In particular, we exploit the Connectionist Temporal Classification (CTC) to compress the input sequence according to its phonetic characteristics. Our experiments demonstrate that our solution brings a 1.3-1.5 BLEU improvement over a strong baseline on two language pairs (English-Italian and English-German), contextually reducing the memory footprint by more than 10%.Comment: Accepted at EACL202

The ITC-irst statistical machine translation system for IWSLT-2004

Focus of this paper is the system for statistical machine translation developed at ITC-irst. It has been employed in the evaluation campaign of the International Workshop on Spoken Language Translation 2004 in all the three data set conditions of the Chinese-English track. Both the statistical model underlying the system and the system architecture are presented. Moreover, details are given on how the submitted runs have been produced. 1