Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+language:
+- en
+- es
+- sm
+- ypk
+---
+
+# Dataset Card for Dataset Name
+
+**Status: Design-stage dataset card (pre-annotation, pre-evaluation)**
+
+Dataset Card for AAPB Low-Resource Language Identification Dataset (v0)
+
+This dataset contains archival broadcast audio from the American Archive of Public Broadcasting (AAPB),
+curated for evaluating language identification (LID) systems on low-resource languages in realistic
+archival conditions. The initial focus is on Samoan, Yupik, and Spanish.
+
+This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
+
+## Dataset Details
+
+### Dataset Description
+
+The AAPB Low-Resource Language Identification Dataset is a collection of real-world broadcast audio
+drawn from the American Archive of Public Broadcasting (AAPB). The dataset is designed to support
+evaluation of existing off-the-shelf language identification models on low-resource languages under
+challenging archival conditions, including code-switching, non-speech segments, and variable audio
+quality.
+
+This dataset card represents a design-stage (v0) description. Annotation and evaluation are ongoing,
+and quantitative results will be added iteratively in future versions.
+
+
+- **Curated by:** Brandeis University, in collaboration with GBH and the CLAMS project
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+
+### Dataset Sources [optional]
+
+<!-- Provide the basic links for the dataset. -->
+
+- **Repository:** [TBD – internal CLAMS / Brandeis repositories]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the dataset is intended to be used. -->
+
+### Direct Use
+
+<!-- This section describes suitable use cases for the dataset. -->
+This dataset is intended for:
+- Evaluation of existing language identification (LID) models on selected low-resource languages
+- Analysis of LID model behavior on archival broadcast audio
+- Studying the effects of code-switching, non-speech segments, and acoustic variability on LID output
+- Integration with the CLAMS evaluation framework for reproducible benchmarkin
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
+This dataset is not intended for:
+- Training new language identification models
+- Speaker identification or speaker profiling --?
+- Commercial deployment or monetization
+- Applications requiring fine-grained speaker attribution or demographic inference --?
+
+[More Information Needed]
+
+## Dataset Structure
+
+<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
+The dataset consists of audio items corresponding to AAPB broadcast programs or program segments.
+Each item may contain multiple speakers, multiple languages, and non-speech content such as music.
+
+Annotations, where present, are stored in [?]format and represent
+time-aligned language labels for speech segments.
+
+At the current stage, the dataset is not split into train/validation/test partitions, as it is
+primarily intended for evaluation rather than training.
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+<!-- Motivation for the creation of this dataset. -->
+This dataset was created to address the lack of benchmarks for language identification on low-resource
+languages in realistic archival contexts. Many existing datasets focus on clean or synthetic speech,
+which does not reflect the conditions encountered in broadcast archives.
+
+By using authentic AAPB material, this dataset aims to surface practical failure modes and limitations
+of current LID systems.
+
+
+[More Information Needed]
+
+### Source Data
+
+<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
+
+#### Data Collection and Processing
+
+<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
+Audio data was selected from AAPB holdings based on:
+- Likely presence of the target language(s)
+- Sufficient duration for language identification analysis
+- Representation of real broadcast conditions
+- (Minimal normalization is applied in order to preserve the acoustic characteristics of archival audio).
+
+[More Information Needed]
+
+#### Who are the source data producers?
+
+<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
+The source data was produced by human speakers participating in broadcast programs, including hosts,
+interviewees, and callers. Demographic or identity information about speakers is generally unknown and
+is not inferred. The data was originally created for broadcast and archival purposes, not for machine learning.
+
+[More Information Needed]
+
+### Annotations [optional]
+
+<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
+
+#### Annotation process
+
+<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
+Annotation focuses on identifying the language of speech segments relevant for LID evaluation.
+Annotations are being introduced incrementally and may be refined based on pilot evaluation results.
+Annotation guidelines are under development and may evolve as new error patterns are observed.
+[More Information Needed]
+
+#### Who are the annotators?
+
+<!-- This section describes the people or systems who created the annotations. -->
+Annotations are produced by human annotators fluent or native in the target languages, including
+(summer) fellows recruited for Spanish, Samoan, and Yupik. Annotators are selected based on language
+proficiency.
+
+[More Information Needed]
+
+#### Personal and Sensitive Information
+
+<!-- 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. -->
+The dataset consists of publicly archived broadcast material. No additional personal or sensitive
+information is intentionally added during annotation. Speakers may be identifiable as part of the
+original broadcast context, but no attempts are made to infer or augment personal attributes.
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+This dataset has several known limitations:
+- Small sample sizes for low-resource languages
+- Language imbalance and frequent code-switching with English
+- Presence of non-speech content such as music and background noise
+- Variability in recording quality across archival programs
+- Potential ambiguity at segment boundaries during annotation
+
+These limitations should be considered when interpreting evaluation results.
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
+
+Users are encouraged to:
+- Treat evaluation results as indicative rather than definitive
+- Avoid overgeneralizing findings beyond archival broadcast contexts
+- Report observed biases or failure modes in downstream analyses
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Dataset Card Authors [optional]
+
+[More Information Needed]
+
+## Dataset Card Contact
+Yangyang Chen (Brandeis University), with contributions from GBH and CLAMS collaborators
+
+[More Information Needed]