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Dataset results
2 results for “oral corpus”
Oral cancer speech corpus for paper "Detecting and analysing spontaneous oral cancer speech in the wild"
<p>This is the oral cancer speech corpus used in the paper <em>"Detecting and analysing spontaneous oral cancer speech in the wild".</em></p> <p><strong>Description</strong></p> <p>This dataset contains approximately 3 hours of oral cancer speech data collected from YouTube, including a file with additional metadata. We use this dataset to perform an oral cancer speech detection task in our paper.</p> <p><strong>Funding</strong></p> <p>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No 766287. The Department of Head and Neck Oncology and surgery of the Netherlands Cancer Institute receives a research grant from Atos Medical (Horby, Sweden),<br> which contributes to the existing infrastructure for quality of life research.</p> <p><strong>Citation:</strong></p> <p>If you use this dataset please cite:</p> <pre><code>@misc{halpern2020detecting, title={Detecting and analysing spontaneous oral cancer speech in the wild}, author={Bence Mark Halpern and Rob van Son and Michiel van den Brekel and Odette Scharenborg}, year={2020}, eprint={2007.14205}, archivePrefix={arXiv}, primaryClass={eess.AS} }</code></pre> <p> </p>
Oral cancer speech corpus for the paper "Objective speech outcomes after surgical treatment for oral cancer: An acoustic analysis of a spontaneous speech corpus containing 32.850 tokens"
<p>Dataset accompanying the paper "<em>Objective speech outcomes after surgical treatment for oral cancer: An acoustic analysis of a spontaneous speech corpus containing 32.850 tokens</em>"</p> <p>The zip file contains five folders:</p> <p>- <strong>Database:</strong> contains csv files for each speaker which contain the processed features</p> <p>- <strong>Recordings: </strong>the original recording from the YouTube Oral Cancer speech dataset, without further preprocessing</p> <p>- <strong>Recordings_Normalised:</strong> same as recordings but after minimal audio preprocessing (min-max scaling)</p> <p>- <strong>Textgrids: </strong>contains the textgrids which are annotated on the word-level and on phoneme-level</p> <p>- <strong>TIMIT selection: </strong>contains the textgrids for the TIMIT speakers. We unfortunately cannot share the audio date as it is not open source. More information can be found <a href="https://catalog.ldc.upenn.edu/LDC93s1">here.</a></p>
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