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859 results for “Speeches”
PHENOMENON OF EUPHEMISM AND ITS FUNCTIONS IN SPEECH
<p>This article provides an overview of the historical definition, motives, functions and linguistic tools of euphemism. It also talks about the most effective and common types of euphemisms.</p>
THE ROLE OF HOME READING IN FORMING FOREIGN LANGUAGE SPEECH SKILLS IN ENGLISH LESSONS
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SPEECH CLICHES AS A COMPONENT OF EXPRESSIVE ORAL SPEECH
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SPEECH GENRES OF CONGRATULATIONS, PRAISE AND COMPLIMENTS
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COMPARATIVE STUDY OF PARTS OF SPEECH IN MODERN ENGLISH AND UZBEK
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THE INVESTIGATION OF PARALINGUISTIC AND EXTRALINGUISTIC MEANS OF SPEECH
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DIRECT SPEECH IN FRENCH AND ITS MODES OF USE
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A REPRESENTATIVE SPEECH ACT
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THE ROLE OF J. SEARLE IN THE FORMATION OF THE THEORY OF SPEECH ACTS
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TECHNOLOGY OF TEACHING FOREIGN LANGUAGE DIALOGIC SPEECH
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ANALYSIS OF POLITICAL SPEECHES AND ADDRESSES BASED ON SELECTED LINGUISTIC TOOLS
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Audio samples from generative models trained on the TIMIT speech data.
<p>The snippets include samples and reconstructions. All samples are completely unconditional and utilise only the prior internal representations learned by the models. Reconstructions are computed from a given test audio snippet by first encoding it to a learned representation and then decoding that to a reconstruction of the audio.</p> <p>All models are trained on the TIMIT speech dataset (<a href="https://catalog.ldc.upenn.edu/LDC93s1">https://catalog.ldc.upenn.edu/LDC93s1</a>). Some snippets are from models trained at different temporal resolutions denoted by `s1` and `s64`. We refer to the paper for details.</p> <p>The files include:</p> <ul> <li>`clockwork-vae-s64-reconstruction-*` <ul> <li>Four reconstructions using a two-layered Clockwork VAE trained with temporal resolution s=64.</li> </ul> </li> <li>`clockwork-vae-s64-sample-*` <ul> <li>Four samples from the prior of a Clockwork VAE trained with temporal resolution s=64.</li> </ul> </li> <li>`original-*` <ul> <li>Four original samples from TIMIT corresponding in pairs to the reconstructions.</li> </ul> </li> <li>`vrnn-s64-sample-*` <ul> <li>Two samples from the prior of a VRNN trained with temporal resolution s=64.</li> </ul> </li> <li>`vrnn-s1-sample-*` <ul> <li>Two samples from the prior of a VRNN trained with temporal resolution s=1.</li> </ul> </li> <li>`srnn-s64-sample-*` <ul> <li>Two samples from the prior of a SRNN trained with temporal resolution s=64.</li> </ul> </li> <li>`srnn-s1-sample-*` <ul> <li>Two samples from the prior of a SRNN trained with temporal resolution s=1.</li> </ul> </li> <li>`wavenet-s64-sample-*` <ul> <li>Four samples from a WaveNet trained with temporal resolution s=1.</li> </ul> </li> <li>`wavenet-s1-sample-*` <ul> <li>Two samples from a WaveNet trained with temporal resolution s=64.</li> </ul> </li> </ul>
Picture materials of anthropomorphic animals for the use in speech production and perception experiments
<p>These picture materials consist of 10 sets à 4 drawn similar yet slightly different pictures. The picture materials were designed as stimuli for the use in speech production and perception experiments and depict different anthropomorphic animals in curious situations. All pictures are available as JPEG and PNG files.</p>
VIVOS: Vietnamese Speech Corpus for ASR
<p><strong>VIVOS Corpus</strong></p> <p>VIVOS is a free Vietnamese speech corpus consisting of 15 hours of recording speech prepared for Automatic Speech Recognition task.</p> <p>The corpus was published by AILAB, a computer science lab of VNUHCM - University of Science, with <strong>Prof. Vu Hai Quan</strong> is the head of.</p> <p>We publish this corpus in hope to attract more scientists to solve Vietnamese speech recognition problems. The corpus should only be used for academic purposes.</p> <p><strong>License</strong></p> <p>Creative Commons Attribution NonCommercial ShareAlike v4.0 (CC BY-NC-SA 4.0) (<a href="https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode">details</a>)</p> <p><strong>Associated paper</strong></p> <p>Please cite this paper when using VIVOS corpus for research</p> <p>"A non-expert Kaldi recipe for Vietnamese Speech Recognition System", Hieu-Thi Luong and Hai-Quan Vu, in Proc. <em>WLSI/OIAF4HLT2016</em> (<a href="https://aclanthology.org/W16-5207/">paper</a>)</p> <p><strong>Contact</strong></p> <p><a href="mailto:ailab@hcmus.edu.vn">ailab@hcmus.edu.vn</a></p> <p> </p> <p><strong>Corpus properties</strong></p> <p>Speech was recorded in a quiet environment with high quality microphone, speakers were asked to read one sentence at a time.</p> <table> <thead> <tr> <th scope="col"> </th> <th scope="col">Training</th> <th scope="col">Testing</th> </tr> </thead> <tbody> <tr> <td>Speakers</td> <td>46</td> <td>19</td> </tr> <tr> <td>Male</td> <td>22</td> <td>12</td> </tr> <tr> <td>Female</td> <td>24</td> <td>7</td> </tr> <tr> <td>Utterances</td> <td>11660</td> <td>760</td> </tr> <tr> <td>Duration</td> <td>14:55</td> <td>00:45</td> </tr> <tr> <td>Unique Syllables</td> <td>4617</td> <td>1692</td> </tr> </tbody> </table> <p><br> <strong>Evaluations</strong></p> <p>The corpus was evaluated using our non-expert recipe for Vietnamese Speech Recognition system which is described in the associated paper.</p> <table> <thead> <tr> <th scope="col"> </th> <th scope="col">baseline</th> <th scope="col">+pitch</th> <th scope="col">+tone</th> </tr> </thead> <tbody> <tr> <td>mGMM</td> <td>19.66</td> <td>15.14</td> <td>14.91</td> </tr> <tr> <td>mGMM+MMI</td> <td>18.08</td> <td>14.96</td> <td>13.91</td> </tr> <tr> <td>mGMM+SAT</td> <td>15.79</td> <td>12.07</td> <td>12.13</td> </tr> <tr> <td>mDNN+SAT</td> <td>13.34</td> <td>9.54</td> <td>9.48</td> </tr> </tbody> </table> <p><strong>Notice</strong></p> <p>This is the official replacement for http://ailab.hcmus.edu.vn/vivos/</p> <p> </p>
THE PROBLEM OF DEVELOPING THE SPEECH SKILLS OF STUDENTS LEARNING A FOREIGN LANGUAGE IN VOCATIONAL SCHOOLS
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Fluent speech commands dataset
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THE STATUS OF ADVERBS AS A PART OF SPEECH
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MECHANISMS OF SPEECH TECHNIQUE AND SPEECH CULTURE DEVELOPMENT IN FUTURE MILITARY EDUCATORS
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VIEWS OF MAHMUD AZ-ZAMAKSHARI ON SPEECH ETIQUETTE
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SPEECH EXPANDERS
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