Sentence examples for challenge baselines from inspiring English sources

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The Challenge baselines make use of MFCC features concatenated with their first- and second-order derivatives and bigram LMs.

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In LPS group, plasma samples were collected before LPS challenge (baseline) and at the time when ARDS model had been well established (T0).

While the performance of the challenge baseline GMM-HMM system with multi-condition training and constrained maximum likelihood linear regression (CMLLR) achieved a WER of 49.2 % for the real recordings, the best performing system achieved 9.0 % using eight microphones.

Table 2 Category of the REVERB challenge speech recognition task   Type Processing scheme Full batch, utterance-based, real-time Training data of acoustic model Own dataset, multi-condition, clean Recognizer type own recognizer,   Challenge baseline recognizer Number of channels used 1, 2, 8 Italicized data denotes the category to which this paper belongs.

In (34), T d has been set to 80 ms. The performance of the proposed system for each condition is evaluated in terms of instrumental speech quality measures (cf. Section 6.2) as well as in terms of word error rate (WER) when using the proposed system as a preprocessing scheme for the REVERB challenge baseline ASR system (cf. Section 6.3).

Participants were allowed to take part in either (or both) single-channel and multichannel tasks by employing any input features, acoustic models, training criteria, decoding strategies, and advanced single-channel/multichannel front-end processing technologies, which could be completely different from the challenge baseline ASR systems.

Compared to the REVERB challenge baseline results of the final evaluation test set, an absolute improvement of average word error rate (WER) of 12.43 % in the utterance-based batch processing mode and of 9.42 % in the full batch processing mode were achieved in [12].

In the result, deep bidirectional LSTM networks processing log Mel filterbank outputs deliver best results with clean models, reaching down to 42% word error rate (WER) at signal-to-noise ratios ranging from −6 to 9 dB (multi-condition CHiME Challenge baseline: 55% WER).

Ex-vivo LPS challenge baseline assessments were compared by ANOVA followed by Dunnetts multiple comparison test.

Prior to the HFD challenge, baseline measurements of glucose disposal assessed by an OGTT were measured in 21 week old mice and the OGTT was repeated at the end of the HFD challenge at 27 weeks of age.

Lastly, cardiac arrhythmias were identified qualitatively based on our previous findings (Farraj et al. 2011) and the Lambeth convention criteria (Walker et al. 1988), counted, and totaled for the duration of the dobutamine challenge (baseline, treatment, and recovery).

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