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@@ -206,7 +206,7 @@ The annotation process combined both automated and manual methods. It consisted
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  - Alignments: Word- and phoneme-level alignments were created using WebMAUS, which produced TextGrids that aligned the transcriptions with corresponding audio files.
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  - Speaker metadata: The speaker metadata were collected before the recording sessions through the Linguistic History Questionnaire (LHQ) and supplementary forms provided to participants. These forms were designed to capture detailed linguistic and demographic information, ensuring a comprehensive profile of each speaker.
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  - Audio metadata: The audio metadata were automatically captured during the recording process by the equipment used for data collection and embedded into the corresponding audio files.
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  #### Who are the annotators?
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  <!-- This section describes the people or systems who created the annotations. -->
@@ -224,19 +224,22 @@ While the majority of annotations were generated using automated tools, the anno
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  <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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- [More Information Needed]
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  ## Bias, Risks, and Limitations
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
 
 
 
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  ### Recommendations
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- [More Information Needed]
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  ## Dataset Card Authors
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  - Alignments: Word- and phoneme-level alignments were created using WebMAUS, which produced TextGrids that aligned the transcriptions with corresponding audio files.
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  - Speaker metadata: The speaker metadata were collected before the recording sessions through the Linguistic History Questionnaire (LHQ) and supplementary forms provided to participants. These forms were designed to capture detailed linguistic and demographic information, ensuring a comprehensive profile of each speaker.
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  - Audio metadata: The audio metadata were automatically captured during the recording process by the equipment used for data collection and embedded into the corresponding audio files.
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  #### Who are the annotators?
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  <!-- This section describes the people or systems who created the annotations. -->
 
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  <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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+ During the recordings, the participants were asked not to disclose any personal or sensitive information, which was especially relevant for the tasks eliciting free speech. The remaining tasks based on text reading did not contain any personal or sensitive information.
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  ## Bias, Risks, and Limitations
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+ Potential biases in this dataset include:
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+ - Participant demographics: The majority of participants were young adults aged 18 to 25.
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+ - Gender distribution: Women constituted 68% of the speakers.
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+ - Linguistic scope: The speech samples are limited mostly to three languages under investigation, i.e., Norwegian, English, and Polish.
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  ### Recommendations
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+ We recommend to use the set of short audio files (under 30s) for any subsequent analysis. The raw recordings of full tasks can be found [TBA].
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  ## Dataset Card Authors
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